Research ArticleMultiobjective Optimization Model for Sustainable WasteManagement Network Design

Sun Olapiriyakul Warut Pannakkong Warith Kachapanya and Stefano Starita

School of Manufacturing Systems and Mechanical Engineering Sirindhorn International Institute of TechnologyThammasat University PathumThani 12121 Thailand

Correspondence should be addressed to Stefano Starita stefanosiittuacth

Received 14 December 2018 Revised 11 March 2019 Accepted 14 April 2019 Published 13 May 2019

Guest Editor Jesica de Armas

Copyright copy 2019 SunOlapiriyakul et alThis is an open access article distributedunder theCreativeCommonsAttribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Inefficient or poorly planned waste management systems are a burden to society and economy For example excessively long wastetransportation routes can have a negative impact on a large share of the population This is exacerbated by the rapid urbanizationhappening worldwide and in developing countries Sustainability issues should be accounted for at every stage of decision makingfrom strategic to daily operations In this paper we propose a multiobjective optimization model to design a cost-effective wastemanagement supply chain while considering sustainability issues such as land-use and public health impactsThemodel is appliedto a case study in PathumThani (Thailand) to provide managerial insights

1 Introduction

An unsanitary and inefficient municipal solid waste manage-ment (MSWM) system has long been a challenging issue toovercome An inadequate waste management budget and thelack of public participation in waste segregation at the sourceare among the leading causes for the long-term accumulationof uncollected and improperly disposed of solid wastes indeveloping countries In urban areas unsanitary disposalsites are generally more problematic considering the limitedland availability and the need to attain adequate wastedisposal capacity to serve a rapidly growing populationThe risk of exposure to contaminants emitted from solidwaste disposal is also more pronounced for urban residentsFirst this is due to the problem of waste disposal capacityshortage caused by a lack of land suitable for solid wastereceptacles or a delay in building sufficient capacity Wasteflows beyond manageable capacity are among the causesof the uncontrolled release of leachates and gases whichcan lead to the formation of strong unpleasant odors andspontaneous fires Second in an urban context expandingthe existing disposal facilities or locating new ones has to bemade in the vicinity of densely populated areas The releaseof hazardous constituents from disposal and transport oper-ations can impose substantial environmental stress on the

surrounding communities especially for centralized MSWMsystems [1] The neighboring population has to deal withthe immediate impacts such as uncleanliness odors andinadequate air quality The long-term impacts of unsanitaryMSWM practices on the local population include varioushealth risks [2] and decreased environmental quality [3]

Previous studies highlight the fact that in developingcountries MSWM results in decreasing property values [4]and imposes an additional financial burden on the local pop-ulation in terms of higher sanitation fees [5] Consequentlya disproportionate environmental impact is an increasinglyimportant issue in MSWM planning To resolve this issueenvironmental justice must be added as one of the strategicgoals to be achieved The principles of environmental justicein this case refer to the idea that all communities must beprotected from excessive or disproportionate environmentalstressors The level of environmental stressors experiencedby communities needs to be evaluated Whenever possiblethe capacity of each community to tolerate unfavorableenvironmental impacts should be considered

Aside from disproportionate impacts and justice con-cerns the negative externalities of MSWM can also impedethe development of desired social aspects such as strongcommunity social cohesion and efficient youth development[6] The waste management literature [7] also reveals that

HindawiJournal of Advanced TransportationVolume 2019 Article ID 3612809 15 pageshttpsdoiorg10115520193612809

2 Journal of Advanced Transportation

environmental problems of waste management generate anumber of social issues such as those related to employmentopportunities [8] unsanitary working conditions [9] andcommunity satisfaction [10] Attempts to offset these issuesusually require significant spending on improving sanitaryinfrastructure and services Such financial needs can ulti-mately leave communities with an insufficient sanitary bud-get and inability to properly collect and dispose of municipalsolid wastes leading to a vicious cycle of decline in localpublic health and environmental conditions Therefore asustainable MSWN requires that significant economic envi-ronmental and social issues be integrated into the strategicdecision-making processes

The successful establishment of sustainable MSWM isdependent on the network design and transportation plan-ning stage Environmentally benign site selection requiresa careful land suitability analysis The potential interac-tions of disposal sites with local communities and existinggeographical hydrological and socioeconomic parametersneed to be taken into account For example in Thailandthere is a rigorous protocol for solid waste disposal siteselection However a large number of disposal sites arestill located in environmentally sensitive areas Due to therapid and unplanned urban growth in many cities somedisposal sites which were originally in suitable vacant landareas are now in close proximity to rapidly urbanizing areasUnder the current MSWM situation the number of affectedcommunities is only expected to rise in the near future Localgovernments will also expend a great deal of effort to copewith strong public opposition should any future solid wastedisposal siting or expansion decision be taken To sum upa sustainable MSWM requires the development of networkdesign approaches to help in resolving the following MSWMchallenges

(i) finding suitable land for waste disposal(ii) public health impacts caused by the operation of

MSWM facilities and waste transport(iii) lack of land-use planning for MSWM(iv) environmental justice and disproportionate environ-

mental impacts on nearby communities

The remainder of the paper is organized as followsSection 2 provides a review of the relevant literature Section 3introduces a mixed-integer multiobjective program to designa sustainable supply chain for waste management A casestudy in Pathum Thani (Thailand) province is analyzedin Section 4 Finally the conclusion and future researchdirections are discussed in Section 5

2 Background

This section provides a literature review to gain an insight intothe research trends in sustainable MSWM design We focuson three broad categories sustainable supply chain networkdesign (SCND) solid wastemanagement and environmentaljustice Results are summarized in aVenn diagram in Figure 1The diagram reveals that each research field has received

SustainableSCND

1122

19(4)Environmental

justice2851

Solid waste18144

18(7)

23(6)

Figure 1 Relevant research areas

considerable attention over the yearsThere are somepairwiseoverlaps However to the best of our knowledge no researchpaper has studied the problem incorporating the three issuesat the same time

Despite a growing research interest in sustainable supplychain management and environmental justice there is stilllimited consideration of environmental justice issues in thesustainable SCND literature Past studies combine equalityand justice issues with the environmental and social dimen-sions Moura et al [11] incorporate environmental justiceaspects into a biobjective transportation network designmodel while addressing the (three pillars of) sustainabilityTheir model uses a restrictive constraint that protects thesurrounding communities from being overly burdened withnoise and air pollution Themotorists cost of increased traveltime due to the congestion effects of the transport network isregarded as the social impactmetric Constraints are imposedto achieve a network design with desired environmentaljustice levels There are also previous sustainable SCNDstudies that investigate social justice issues These papersgenerally aim to minimize the inequality in accessing publicservices and in the quality-of-life improvement opportuni-ties An SCND study by Ferguson et al [12] shows howto incorporate social equality into a transit service designproblem They aim to minimize the variation in the level ofaccess to basic amenities provided by the designed transitsystem Jafari et al [13] propose a sustainable SCNDmodel fortextile industries with the aim of promoting social justice bymaximizing the employment level in different geographicalareas Despite the increased research efforts there are stillsocial justice issues that need to be translated into a well-defined optimization problem Manaugh et al [14] pointout social justice issues and measures that can potentiallybe incorporated into urban transport planning These issuesare related to the disproportionate accessibility of transportservice among different groups of people Oswald Beilerand Mohammed [15] address many demographic social-economic and location-based factors that can be consideredin developing transportation justice metrics and frameworks

The topic of solid waste management has been studiedin depth due to the steadily growing urban populationand consequent waste generation Life-cycle environmentalimpacts of various MSWM systems have been explored

Journal of Advanced Transportation 3

extensively as reviewed by Bernstad Saraiva et al 2018 [16]Also a number of economic environmental and socialperformance indicators for MSWM have been proposedby researchers as addressed by Rodrigues et al 2018 [17]However most of sustainable SCND studies are related toindustrial applications The strategic planning of MSWMinfrastructures and transport network has been confined tothe analysis of infrastructure investment operating expensesand economic viability For instance Zhang et al [18] developan optimization model to minimize the costs of inventorytransportation and disposal of MSWM In their study aninterval programming approach is employed to deal withuncertainties of MSWM planning parameters Toso andAlem [19] propose a deterministic and stochastic capacitatedfacility location model to determine the optimal locationplanning design for recycling urban solid wastes Theirmodel solely focuses on minimizing the overall costs havingbudget constraints Just recently more attention is being givento MSWM planning problems looking beyond economicfeasibility to add the sustainability perspective A networkdesign study by Inghels et al [20] evaluates the financialviability of using multimodal transportation to reduce thecarbon emissions and social impact of MSWM Their modelevaluates the societal cost burden associated with differenttransportation modes measured as the sum of disturbanceeffects on nearby residents The effects include accidentsnoise air pollution congestion and construction of transportinfrastructure Xu et al [21] propose a SCND model for thereverse logistic supply chain of solid wastes The amountof carbon emissions created during the transportation ofrecyclable e-wastes is used as an environmental metric

The number of affected people is used to estimate thenegative effects of MSWM facilities on local communitiesAccording to the research trend all aspects of sustainabilityare currently being addressed in the context of MSWMHowever as pointed out by Eskandarpour et al [22] thereis a research need for a broader consideration of social andenvironmental impactmatrices Aside from the global warm-ing potential the use of other LCA-based environmentalimpact indicators needs to be explored Indicators that havebeen used by LCA studies to evaluate the environmentalperformance of MSWM systems are summarized in thereview papers by Khandelwal et al [23] and Yadav andSamadder [24]

As already pointed out there is a lack of studies abouthow justice affects the sustainability performances of anMSWM system The development of MSWM infrastructurethat positively contributes to environmental and social justicemust be based on a careful evaluation of the current stageof urban development and ongoing injustice issues [25ndash27] There is a difference between social and environmentaljustice problems in developed and developing countriesDeveloped countries generally experience inequalities forside effects of urban growth such as air pollution wastewater and traffic congestion In developing countries andlow-density cities the problems are more related to spatialinequalities of economic development activities sanitationservices and allocation of public resources As shown inthe case of the Perth Metropolitan area people living in

the outer suburbs have the least accessibility provided bycar and public transport to job education shopping andhealthcare opportunities [28] The case of plastic bag wastein Nairobi Kenya is a typical example of environmentaljustice issues associated with the disproportionate share ofsanitary services and environmental protection policy [29]The case study describes how political influences on localbusinesses result in unsustainable patterns of production andconsumption of plastic bags and thereby there is a vastaccumulation of solid and plastic wastes in communities withlow socioeconomic status

In addition to pollution problems land-use issues arealso critical issues in MSWM planning Agyeman and Evans[30] explore urban development initiatives that demonstrateinherent links between environmental justice and sustain-ability issues They point out that solid waste and land-use planning are common concerns for both environmentaljustice and sustainability A land-use policy should focuson preventing disproportionate land-use impacts within oramong communities Without adequate land-use and envi-ronmental justice policies solid waste facilities are likely tobe located in poor and minority communities as discoveredby Norton et al [31] when focusing on North Carolina wasteinfrastructure

This study addresses the three fundamental sustainabilitydimensions environmental social and economic in thecontext of MSWM in rapidly urbanized regions To bridgethe research gap and contribute to the field of sustainableMSWM this develops a social impact metric based onenvironmental justice and incorporate it into a sustainableSCND model for MSWM system Specifically the issue ofenvironmental justice related to land-use stress caused byMSWM facility establishment is considered The inclusionof a land-use equality objective is used to obtain a balancednetwork design where land-use stress is fairly distributedacross an area Furthermore the damage ofMSWMtohumanhealth is also introduced as a measure for the environmentalimpact of an MSWM system We use the disability-adjustedlife years (DALYs) metric according to the life-cycle impactassessment (LCIA) method Despite being used by WHO asa measure of the global burden of disease for many yearsthere have been very limited applications of DALYs in boththe supply chain and the waste management literature Lastlyfacility and transportation costs are taken into account toevaluate the economic aspects of sustainability

3 Methodology

31 Public Health Impact Assessment In this study the publichealth impact is defined as the overall mortality and diseaseburden of nearby residents caused by MSWM facilitiesand waste transport activities The public health impact isestimated in units of disability-adjusted life years (DALYs)which is one of the well-established endpoint LCIA metricsDALYs represent the number of years of life lost due topremature mortality and healthy years of life lost due todisability [32] We translate the impact of waste managementoperations and waste transportation into DALYs per person

4 Journal of Advanced Transportation

Landfills

Incinerators

Recycling by private companies

Sorting facilities

Collection centers

transport by small truck

transport by large truck

transportationcost

transportationcost

disposal

seperation

collection

Figure 2 Waste management supply chain

using the ReCiPe 2008 Endpoint LCIA method [33] Thenthe total DALYs are obtained by multiplying the individualimpact of exposure by the total number of people livingwithin the affected area

32 Land-Use Impact Assessment Processes in MSWM facil-ities including construction operation and closure normallytake place over long timescales Under traditional centralizedwaste systems the life expectancy of MSWM facilities islonger due to the need for larger-sized facilities to copewith increased waste generation in cities Communitiessurrounding waste facilities have to deal with the long-termnegative external effects of municipal solid waste Thereforethe issue of disproportionate environmental burden amongpopulation in certain areas is a pressing concern especiallyfor rapidly urbanized cities From a strategic point of viewit is important that each administrative area in a city isnot overly burdened by land-use impact or other importantenvironmental stressors caused by MSWM facilities Theprinciple of environmental justice must be adopted at theearly phase of MSWM planning

In this study the spatial planning of MSWM infrastruc-ture uses a land-use equality strategy to mitigate the impacton local land-use in areas with substantial land-use stressThe proposed planning approach involves a two-step processThe first step is to evaluate the current land availability ineach geographical or administrative area within a city This

step generally requires knowledge of land-use policies and theuse of GIS tools to screen out portions of land which are notsuitable for development The second step is to calculate theland-use stress of each administrative area which is the ratioof land-use impact caused byMSWMfacilities to the availableland In our study the level of land-use impact is calculatedbased on the total amount of direct and indirect land-useThe direct land-use is the actual land area used for facilityestablishment The indirect land-use is estimated by landoccupation LCIA methodology which assesses the impacton land quality over a given period The ReCiPe Midpoint(H) V107Europe ReCiPe H method is used in our study toaccount for the land occupation impact based on the type andcapacity of facilities Previous attempts to integrate direct andindirect land-use impacts have been made in LCA studies toaccount for the relevant land-use impacts [34 35]

33 Optimization Model for Sustainable MSWM In thissection we introduce a mathematical formulation for thesustainable MSWM problem The multiobjective mixed-integer model is a customization of the popular facilitylocation modelWe consider a 3-echelon supply chain wheresolid wastes are gathered in collection centers then movedto sorting facilities and finally sent to either incinerators orlandfills Figure 2 shows an example of this supply chain

We assume that decisions can be made on both locationsand sizes of tier 2 and tier 3 of the supply chain (ie sorting

Journal of Advanced Transportation 5

facilities and landfillsincinerators) This directly affects thecapacity of each facility its land-use and its impact onpublic health The objective is to identify locations sizesand routes to minimize costs land-use and public healthimpact Superscripts 119878 119868 and 119871 are used throughout themathematical formulation to refer to sorting incinerator andlandfill facilities respectively

The modelrsquos notation is given below

Sets and Indices

(i) 119868 is the set of collection centers indexed by 119894(ii) 119869 is the set of sorting facility locations indexed by 119895(iii) 119870 is the set of incinerator locations indexed by 119896(iv) 1198701015840 is the set of landfill locations indexed by 1198961015840(v) 119871(119895) 119871(119896) 119871(1198961015840) are the set of available sizes at loca-

tions 119895 119896 and 1198961015840 indexed by 119897

Parameters

(i) 119905119894119895 119905119895119896 1199051198951198961015840 are the transportation costs on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(ii) 119888119878119895119897 119888119868119896119897 1198881198711198961015840119897 are the fixed costs to open facilities of size 119897

(iii) 119862119878119895119897 119862119868119896119897 1198621198711198961015840119897 are the storage capacities of facilities of

size 119897(iv) 119862119894119895 119862119895119896 1198621198951198961015840 define the maximum amount of waste

that a single trip can carry over links (119894 119895) (119895 119896) and(119895 1198961015840) respectively

(v) 119900119878119895 119900119868119896 1199001198711198951198961015840 are unit operations costs tomanage the flow

of solid waste for each facility(vi) 119904119878119895119897 119904

119868119896119897 1199041198711198961015840119897 are land-use stress ratios for facilities of size

119897(vii) 119863119894 is the amount of solid waste available at collection

center 119894(viii) 119901119894119895 119901119895119896 1199011198951198961015840 are the number of people living nearby

links (119894 119895) (119895 119896) and (119895 1198961015840) respectively(ix) 119901119878119895119897 119901

119868119896119897 1199011198711198961015840119897 are the number of people living near a

facility of size 119897(x) 119889119894119895 119889119895119896 1198891198951198961015840 are the DALYs per person due to trans-

portation activities on links (119894 119895) (119895 119896) and (119895 1198961015840)respectively

(xi) 119889119878119895119897 119889119868119896119897 1198891198711198961015840119897 are the DALYs per person due to size 119897

facility operations

Decision Variables

(i) 119910119878119895119897 119910119868119896119897 1199101198711198961015840119897 are binary location variables equal to 1

when sorting facilities incinerators and landfills ofsize 119897 are open at their respective locations 119895 119896 and1198961015840

(ii) 119909119894119895 119909119895119896 1199091198951198961015840 are the number of trips on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(iii) 119891119894119895 119891119895119896 1198911198951198961015840 denote the amount of solid waste trans-ported on links (119894 119895) (119895 119896) and (119895 1198961015840) respectively

The cost function 119865119888 is computed as follows

119865119888 = sum119895isin119869

sum119897isin119871(119895)

119888119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119888119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11988811987111989610158401198971199101198711198961015840119897

+sum119894isin119868

sum119895isin119869

(119905119894119895 + 119900119878119895) 119909119894119895 +sum

119895isin119869

sum119896isin119870

(119905119895119896 + 119900119868119896) 119909119895119896

+sum119895isin119869

sum1198961015840isin1198701015840

(1199051198951198961015840 + 1199001198711198961015840) 1199091198951198961015840

(1)

The overall cost is the sum of the fixed costs to opensorting facilities incinerators and landfills plus the opera-tional costs of transporting andmanaging the solidwaste flowacross the network

A second function 119865119906 is introduced to measure theaverage land-use stress The function is formally defined asfollows

119865119906 = sum119895isin119869

sum119897isin119871(119895)

119904119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119904119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11990411987111989610158401198971199101198711198961015840119897 (2)

The function is the sum of all the land-use ratio acrossall candidate locations Parameters 119904119895119897 119904119896119897 1199041198961015840119897 represent theratios for land used and land available This ratio can becomputed by looking at the entire network or by narrowingdown the focus to smaller districts to compute the impact ofland-use at a local level

Finally a third function 119865ℎ is used to evaluate the impactof transportation and facilities on the populationrsquos health Thefunction is defined as follows

119865ℎ = sum119895isin119869

sum119897isin119871(119895)

119901119878119895119897119889119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119901119868119896119897119889119868119896119897119910119868119896119897

+ sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

119901119871119896101584011989711988911987111989610158401198971199101198711198961015840119897sum119894isin119868

sum119895isin119869

119901119894119895119889119894119895119909119894119895

+sum119895isin119869

sum119896isin119870

119901119895119896119889119895119896119909119895119896 +sum119895isin119869

sum1198961015840isin1198701015840

119901119895119896101584011988911989511989610158401199091198951198961015840

(3)

The Sustainable Waste Management Network (SWMN)design model can be formulated as a multiobjective mixed-integer program

[SWMN] min 119865119888 119865119906 119865ℎ (4)

st sum119895isin119869

119891119894119895 = 119863119894 forall119894 isin 119868 (5)

sum119894isin119868

119891119894119895 = sum119896isin119870

119891119895119896 forall119895 isin 119869 (6)

6 Journal of Advanced Transportation

sum119894isin119868

119891119894119895 le sum119897isin119871(119895)

119862119895119897119910119878119895119897 forall119895 isin 119869 (7)

sum119895isin119869

119891119895119896 le sum119897isin119871(119896)

119862119896119897119910119868119896119897 forall119896 isin 119870 (8)

sum119895isin119869

1198911198951198961015840 le sum119897isin119871(1198961015840)

11986211989610158401198971199101198711198961015840119897 forall1198961015840 isin 1198701015840 (9)

119891119894119895 le 119862119895119897119909119894119895 forall119894 isin 119868 119895 isin 119869 (10)

119891119895119896 le 119862119896119897119909119895119896 forall119895 isin 119869 119896 isin 119870 (11)

1198911198951198961015840 le 11986211989610158401198971199091198951198961015840 forall119895 isin 119869 119896 isin 119870 (12)

sum119897isin119871(119895)

119910119878119895119897 le 1 forall119895 isin 119869 (13)

sum119897isin119871(119896)

119910119868119896119897 le 1 forall119896 isin 119870 (14)

sum119897isin119871(1198961015840)

1199101198711198961015840119897 le 1 forall1198961015840 isin 1198701015840 (15)

119891119894119895 119891119895119896 1198911198951198961015840 ge 0 forall119894 119895 119896 1198961015840 (16)

119910119878119895119897 119910119868119896119897 y1198711198961015840119897 isin 0 1 forall119895 119896 1198961015840 119897 (17)

119909119894119895 119909119895119896 1199091198951198961015840 isin Z+ forall119894 119895 119896 1198961015840 (18)

The objective (4) is to minimize the costs land-use ratiosand impact of transportation Constraints (5) state that theoutflow of waste from any given collection center 119894 mustbe equal to 119863119894 Equations (6) are flow balance constraintsenforcing that the inflow at a sorting facility 119895 is entirelyforwarded to incinerators 119896 and landfills 1198961015840 Constraints (7)-(9) are the size-dependent capacity constraints at any facilityof the network Constraints (10)-(12) are the transportationcapacity limitations Inequalities (13)-(15) enforce that onlyone size can be selected if a facility is open at a given locationConstraints (16)-(18) define the decision variablesrsquo domains

34 Solution Algorithms The computational results dis-played in Section 4 are obtained from various optimizationmodels solved under single-objective functions and multiob-jective functions We refer to these models using the notationSWMN() where we define inside the brackets the objectivesbeing optimized together For example SWMN(119865119888 119865ℎ) is themultiobjective problem optimizing both costs and healthimpact whereas SWMN(119865119906) is the single-objective modelminimizing only the land-use impact Single-objective mod-els can be solved with numerical methods such as branchand boundmethod As formultiobjective models amin-maxapproach is implemented to identify solutions that minimizethe deviations from the ideal results Formally let 119865lowast119888 119865

lowast119906 and

119865lowastℎ be the optimal value obtained by solving the respectivesingle-objective problems Furthermore let 119865119898119886119909119888 119865119898119886119909119906 and119865119898119886119909ℎ upper bounds be set equal to the worst value obtainedby each function across the single-objective problemsWe can

now define the deviation levels between each objective and itsideal target by normalizing the functions as follows

120590119888 =119865119888 minus 119865lowast119888

119865119898119886119909119888 minus 119865lowast119888(19)

120590119906 =119865119906 minus 119865lowast119906119865119898119886119909119906 minus 119865lowast119906

(20)

120590ℎ =119865ℎ minus 119865lowastℎ119865119898119886119909ℎ

minus 119865lowastℎ

(21)

By adding a new continuous decision variable 119911 we canformulate a min-max goal attainment on the deviations ofthree objectives as follows

[SWMN (119865119888 119865119906 119865ℎ)] min 119911 (22)

st 120590119888 le 119911 (23)

120590119906 le 119911 (24)

120590ℎ le 119911 (25)

(5) minus (18) (26)

The objective of min-max SWMN is to minimize thelargest deviation from optimal targets across the three func-tions considered The model can be easily modified to targetonly two objectives

4 Case Study

In this section we apply the proposed SWMN model to acase study in Pathum Thani province in Thailand The wastemanagement system in Thailand is of interest as very littleplanning has been used in the past to locate waste facilitiesNowadays among a total of 2490 municipal solid wastesites only 499 (20) adopt safety standards such as sani-taryengineer landfill controlled dumping and incinerationwith air pollution-controlled system [36]The rest of the sitesimplement unhealthy practices such as open dumping andincineration without air pollution-controlled system As aconsequence the uncontrolled release of leachates and gasesfrom these dumps is frequent This is taking a toll on bothenvironment and society For example in 2010 a fire brokeout at the Phraeksa dump site causing hundreds of residentsto flee the area This incident prompted local governmentsacross Thailand to reexamine their regulatory approaches inhealth and environmental safety

PathumThani is located in the central region ofThailandwithin the Bangkok metropolitan area (Figure 3) It coversa total area of 15259 km2 organized into 7 districts 60subdistricts and 529 villages Its population has steadilyincreased in the past decade to about 12 million As a resultthe amount of waste generated increased to 0612 milliontonnesyear [36] As the province is quite vast we narrow thefocus toMuang PathumThani SamKhok and Lat LumKaeodistricts for our case study (Figure 4) Currently solid wastesfrom communities are gathered at collection centers across

Journal of Advanced Transportation 7

Table 1 Safety distance from waste facilities

Criteria Sorting facility (km) Incinerator (km) Landfill (km)Residential area 1 2 1Archaeological heritage site 1 1 1River 1 1 1Pond - 03 03Main road - 03 03

Pathum ani

Bangkok

Phra Nakhon Si Ayutthaya

Nakhon Nayok

Saraburi

Nonthaburi

Figure 3 Central Thailand

subdistricts Wastes at collection centers are transported tosorting facilities and subsequently sent to either incineratorsor landfills Recycling is purposely not included in this studyas it is currently done by private companies The validation ofthe proposed model is done by determining the location andsize of sorting and disposal facilities

41 Parameters

Land Availability Assessment and Candidate Locations Inorder to quantify the land available an initial screening isnecessary to exclude from the analysis places such as riverspondsmain roads archaeological heritage sites and residen-tial areas We further include a buffering area to guaranteesafe distances between waste sites As shown in Table 1 thesize of these buffers is set according to the regulation andguideline of MSWM developed by the Pollution ControlDepartment (PCD)

A number of polygons are identified by combiningavailable land with subdistrict boundaries Based on theirsizes these polygons are further divided and their centroidis selected as a facility location Available land for landfillsiting is shown in Figure 4 Since candidate locations ofthe three types of facilities overlap we further constrain themathematical model to avoid colocations

To ensure environmental justice across the three districtswe perform the land-use assessment at the subdistrict levelFor any location within a subdistrict we compute parameters119904119878119895119897 119904119868119896119897 and 119904

1198711198961015840119897 as the following ratio

Direct + Indirect land use with facility of size 119897Total land available in the sub-district

(27)

For each facility 3 capacity levels are considered smallmedium and large Their direct and indirect land-use areshown inTable 2The values are estimated by land occupationLCIA methodology as previously described in our land-useimpact assessment

Traveling Distances All wastes are transported from the col-lection centers to the sorting facilities using 16-tonne (light)trucks From the sorting facilities to both the incineratorand landfill sites 32-tonne (heavy) trucks are used Travelingdistances are estimated using ArcGIS and a digital map ofPathum Thani Specifically having defined the candidatelocations we use a network analysis tool to determine theshortest routes

Public Health Impact Assessment To measure the publichealth impact this study computes the DALYs for peopleaffected by the MSWM system The first step is to estimatethe number of people living near the supply chain No datais currently available showing the population distribution atthe household level ArcGIS is used to count the total numberof residential buildings surrounding the waste transportationroutes and MSWM facilities

To estimate the damage to public health caused by anMSWM system this study adopts the emission-to-exposuremodel used byGouge et al [37] andGreco et al [38]They useseveral buffer distances to estimate the health impact causedby transport pollution In our study we set the buffer distancefor transportation routes to 100m For MSWM facilities theaffected areas are assumed to increase with the waste disposaldimension Moreover due to a long history of unsanitarypractices in Thailand landfills are assumed to have a largerimpact than other MSWM facilities (Table 3)

The estimation of the number of affected people is madebased on the information of the total population living in thearea and the number of residential buildings The proposedestimation approach is expected to give a more accurateestimate of affected people than the previous approach [39]Varying impact distances corresponding to different typesand sizes of facilities are used instead of one single impactdistanceThe second step is tomultiply the number of affected

8 Journal of Advanced Transportation

Nonthaburi

Bangkok

Pathum ani

Candidate landfill siting locationsUnsuitable area for landfill siting

Figure 4 Landfill locations

Table 2 Direct and indirect land-use impacts

Direct land-use (1198982) Indirect land-use (1198982)Waste facility Small size Medium size Large size Small size Medium size Large sizeSorting facility 4800 8000 16000 6191 10780 21559Incinerator 8000 16000 24000 11971 23941 35911Landfill 80000 160000 192000 127770 255525 335295

Table 3 Facilities impact on public health

Facilities Sized Capacity (tonneday) Affected areas (km) DALYs

Sorting FacilitySmall 50 03 007

Medium 100 06 014Large 300 18 028

IncineratorSmall 50 05 595

Medium 100 1 119Large 150 15 1785

LandfillSmall 50 1 389

Medium 100 2 778Large 150 3 1166

people near the transportation routes and MSWM facilitiesby the DALYs coefficients which are summarized in Tables 3and 4 The number of DALYs is estimated based on a 30-yearoperational period using the ReCiPe 2008 Endpoint LCIAmethod [33] Only local-scale environmental impacts aretaken into account including human toxicity photochemicaloxidant formation PM formation and ionizing radiationThe damage due to climate change and ozone depletion isneglected Finally the capacity of waste sites and trucks isselected from those available in SimaPro 73 (LCA software)which covers a wide range of typical facilities and operationsThe entire dataset can be found in Kachapanya [40]

42 Results and Discussion This section presents the resultsfrom the computational analysis which is carried out on aWindows 10 machine using an Intel i7-6700HQ processorwith 8GB of RAM CPLEX 126 optimization studio is usedto solve the mathematical models The analysis is organizedin two subsections single-objective and multiobjective opti-mizations

The results are interpreted in terms of satisfaction levelsof each objective A satisfaction level of 100 indicates thatthe objective is equal to its optimal level Conversely smallersatisfaction levels indicate that there is a gap between theobjective and its best achievable target Formally these levels

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

Journal of Advanced Transportation 3

extensively as reviewed by Bernstad Saraiva et al 2018 [16]Also a number of economic environmental and socialperformance indicators for MSWM have been proposedby researchers as addressed by Rodrigues et al 2018 [17]However most of sustainable SCND studies are related toindustrial applications The strategic planning of MSWMinfrastructures and transport network has been confined tothe analysis of infrastructure investment operating expensesand economic viability For instance Zhang et al [18] developan optimization model to minimize the costs of inventorytransportation and disposal of MSWM In their study aninterval programming approach is employed to deal withuncertainties of MSWM planning parameters Toso andAlem [19] propose a deterministic and stochastic capacitatedfacility location model to determine the optimal locationplanning design for recycling urban solid wastes Theirmodel solely focuses on minimizing the overall costs havingbudget constraints Just recently more attention is being givento MSWM planning problems looking beyond economicfeasibility to add the sustainability perspective A networkdesign study by Inghels et al [20] evaluates the financialviability of using multimodal transportation to reduce thecarbon emissions and social impact of MSWM Their modelevaluates the societal cost burden associated with differenttransportation modes measured as the sum of disturbanceeffects on nearby residents The effects include accidentsnoise air pollution congestion and construction of transportinfrastructure Xu et al [21] propose a SCND model for thereverse logistic supply chain of solid wastes The amountof carbon emissions created during the transportation ofrecyclable e-wastes is used as an environmental metric

The number of affected people is used to estimate thenegative effects of MSWM facilities on local communitiesAccording to the research trend all aspects of sustainabilityare currently being addressed in the context of MSWMHowever as pointed out by Eskandarpour et al [22] thereis a research need for a broader consideration of social andenvironmental impactmatrices Aside from the global warm-ing potential the use of other LCA-based environmentalimpact indicators needs to be explored Indicators that havebeen used by LCA studies to evaluate the environmentalperformance of MSWM systems are summarized in thereview papers by Khandelwal et al [23] and Yadav andSamadder [24]

As already pointed out there is a lack of studies abouthow justice affects the sustainability performances of anMSWM system The development of MSWM infrastructurethat positively contributes to environmental and social justicemust be based on a careful evaluation of the current stageof urban development and ongoing injustice issues [25ndash27] There is a difference between social and environmentaljustice problems in developed and developing countriesDeveloped countries generally experience inequalities forside effects of urban growth such as air pollution wastewater and traffic congestion In developing countries andlow-density cities the problems are more related to spatialinequalities of economic development activities sanitationservices and allocation of public resources As shown inthe case of the Perth Metropolitan area people living in

the outer suburbs have the least accessibility provided bycar and public transport to job education shopping andhealthcare opportunities [28] The case of plastic bag wastein Nairobi Kenya is a typical example of environmentaljustice issues associated with the disproportionate share ofsanitary services and environmental protection policy [29]The case study describes how political influences on localbusinesses result in unsustainable patterns of production andconsumption of plastic bags and thereby there is a vastaccumulation of solid and plastic wastes in communities withlow socioeconomic status

In addition to pollution problems land-use issues arealso critical issues in MSWM planning Agyeman and Evans[30] explore urban development initiatives that demonstrateinherent links between environmental justice and sustain-ability issues They point out that solid waste and land-use planning are common concerns for both environmentaljustice and sustainability A land-use policy should focuson preventing disproportionate land-use impacts within oramong communities Without adequate land-use and envi-ronmental justice policies solid waste facilities are likely tobe located in poor and minority communities as discoveredby Norton et al [31] when focusing on North Carolina wasteinfrastructure

This study addresses the three fundamental sustainabilitydimensions environmental social and economic in thecontext of MSWM in rapidly urbanized regions To bridgethe research gap and contribute to the field of sustainableMSWM this develops a social impact metric based onenvironmental justice and incorporate it into a sustainableSCND model for MSWM system Specifically the issue ofenvironmental justice related to land-use stress caused byMSWM facility establishment is considered The inclusionof a land-use equality objective is used to obtain a balancednetwork design where land-use stress is fairly distributedacross an area Furthermore the damage ofMSWMtohumanhealth is also introduced as a measure for the environmentalimpact of an MSWM system We use the disability-adjustedlife years (DALYs) metric according to the life-cycle impactassessment (LCIA) method Despite being used by WHO asa measure of the global burden of disease for many yearsthere have been very limited applications of DALYs in boththe supply chain and the waste management literature Lastlyfacility and transportation costs are taken into account toevaluate the economic aspects of sustainability

3 Methodology

31 Public Health Impact Assessment In this study the publichealth impact is defined as the overall mortality and diseaseburden of nearby residents caused by MSWM facilitiesand waste transport activities The public health impact isestimated in units of disability-adjusted life years (DALYs)which is one of the well-established endpoint LCIA metricsDALYs represent the number of years of life lost due topremature mortality and healthy years of life lost due todisability [32] We translate the impact of waste managementoperations and waste transportation into DALYs per person

4 Journal of Advanced Transportation

Landfills

Incinerators

Recycling by private companies

Sorting facilities

Collection centers

transport by small truck

transport by large truck

transportationcost

transportationcost

disposal

seperation

collection

Figure 2 Waste management supply chain

using the ReCiPe 2008 Endpoint LCIA method [33] Thenthe total DALYs are obtained by multiplying the individualimpact of exposure by the total number of people livingwithin the affected area

32 Land-Use Impact Assessment Processes in MSWM facil-ities including construction operation and closure normallytake place over long timescales Under traditional centralizedwaste systems the life expectancy of MSWM facilities islonger due to the need for larger-sized facilities to copewith increased waste generation in cities Communitiessurrounding waste facilities have to deal with the long-termnegative external effects of municipal solid waste Thereforethe issue of disproportionate environmental burden amongpopulation in certain areas is a pressing concern especiallyfor rapidly urbanized cities From a strategic point of viewit is important that each administrative area in a city isnot overly burdened by land-use impact or other importantenvironmental stressors caused by MSWM facilities Theprinciple of environmental justice must be adopted at theearly phase of MSWM planning

In this study the spatial planning of MSWM infrastruc-ture uses a land-use equality strategy to mitigate the impacton local land-use in areas with substantial land-use stressThe proposed planning approach involves a two-step processThe first step is to evaluate the current land availability ineach geographical or administrative area within a city This

step generally requires knowledge of land-use policies and theuse of GIS tools to screen out portions of land which are notsuitable for development The second step is to calculate theland-use stress of each administrative area which is the ratioof land-use impact caused byMSWMfacilities to the availableland In our study the level of land-use impact is calculatedbased on the total amount of direct and indirect land-useThe direct land-use is the actual land area used for facilityestablishment The indirect land-use is estimated by landoccupation LCIA methodology which assesses the impacton land quality over a given period The ReCiPe Midpoint(H) V107Europe ReCiPe H method is used in our study toaccount for the land occupation impact based on the type andcapacity of facilities Previous attempts to integrate direct andindirect land-use impacts have been made in LCA studies toaccount for the relevant land-use impacts [34 35]

33 Optimization Model for Sustainable MSWM In thissection we introduce a mathematical formulation for thesustainable MSWM problem The multiobjective mixed-integer model is a customization of the popular facilitylocation modelWe consider a 3-echelon supply chain wheresolid wastes are gathered in collection centers then movedto sorting facilities and finally sent to either incinerators orlandfills Figure 2 shows an example of this supply chain

We assume that decisions can be made on both locationsand sizes of tier 2 and tier 3 of the supply chain (ie sorting

Journal of Advanced Transportation 5

facilities and landfillsincinerators) This directly affects thecapacity of each facility its land-use and its impact onpublic health The objective is to identify locations sizesand routes to minimize costs land-use and public healthimpact Superscripts 119878 119868 and 119871 are used throughout themathematical formulation to refer to sorting incinerator andlandfill facilities respectively

The modelrsquos notation is given below

Sets and Indices

(i) 119868 is the set of collection centers indexed by 119894(ii) 119869 is the set of sorting facility locations indexed by 119895(iii) 119870 is the set of incinerator locations indexed by 119896(iv) 1198701015840 is the set of landfill locations indexed by 1198961015840(v) 119871(119895) 119871(119896) 119871(1198961015840) are the set of available sizes at loca-

tions 119895 119896 and 1198961015840 indexed by 119897

Parameters

(i) 119905119894119895 119905119895119896 1199051198951198961015840 are the transportation costs on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(ii) 119888119878119895119897 119888119868119896119897 1198881198711198961015840119897 are the fixed costs to open facilities of size 119897

(iii) 119862119878119895119897 119862119868119896119897 1198621198711198961015840119897 are the storage capacities of facilities of

size 119897(iv) 119862119894119895 119862119895119896 1198621198951198961015840 define the maximum amount of waste

that a single trip can carry over links (119894 119895) (119895 119896) and(119895 1198961015840) respectively

(v) 119900119878119895 119900119868119896 1199001198711198951198961015840 are unit operations costs tomanage the flow

of solid waste for each facility(vi) 119904119878119895119897 119904

119868119896119897 1199041198711198961015840119897 are land-use stress ratios for facilities of size

119897(vii) 119863119894 is the amount of solid waste available at collection

center 119894(viii) 119901119894119895 119901119895119896 1199011198951198961015840 are the number of people living nearby

links (119894 119895) (119895 119896) and (119895 1198961015840) respectively(ix) 119901119878119895119897 119901

119868119896119897 1199011198711198961015840119897 are the number of people living near a

facility of size 119897(x) 119889119894119895 119889119895119896 1198891198951198961015840 are the DALYs per person due to trans-

portation activities on links (119894 119895) (119895 119896) and (119895 1198961015840)respectively

(xi) 119889119878119895119897 119889119868119896119897 1198891198711198961015840119897 are the DALYs per person due to size 119897

facility operations

Decision Variables

(i) 119910119878119895119897 119910119868119896119897 1199101198711198961015840119897 are binary location variables equal to 1

when sorting facilities incinerators and landfills ofsize 119897 are open at their respective locations 119895 119896 and1198961015840

(ii) 119909119894119895 119909119895119896 1199091198951198961015840 are the number of trips on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(iii) 119891119894119895 119891119895119896 1198911198951198961015840 denote the amount of solid waste trans-ported on links (119894 119895) (119895 119896) and (119895 1198961015840) respectively

The cost function 119865119888 is computed as follows

119865119888 = sum119895isin119869

sum119897isin119871(119895)

119888119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119888119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11988811987111989610158401198971199101198711198961015840119897

+sum119894isin119868

sum119895isin119869

(119905119894119895 + 119900119878119895) 119909119894119895 +sum

119895isin119869

sum119896isin119870

(119905119895119896 + 119900119868119896) 119909119895119896

+sum119895isin119869

sum1198961015840isin1198701015840

(1199051198951198961015840 + 1199001198711198961015840) 1199091198951198961015840

(1)

The overall cost is the sum of the fixed costs to opensorting facilities incinerators and landfills plus the opera-tional costs of transporting andmanaging the solidwaste flowacross the network

A second function 119865119906 is introduced to measure theaverage land-use stress The function is formally defined asfollows

119865119906 = sum119895isin119869

sum119897isin119871(119895)

119904119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119904119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11990411987111989610158401198971199101198711198961015840119897 (2)

The function is the sum of all the land-use ratio acrossall candidate locations Parameters 119904119895119897 119904119896119897 1199041198961015840119897 represent theratios for land used and land available This ratio can becomputed by looking at the entire network or by narrowingdown the focus to smaller districts to compute the impact ofland-use at a local level

Finally a third function 119865ℎ is used to evaluate the impactof transportation and facilities on the populationrsquos health Thefunction is defined as follows

119865ℎ = sum119895isin119869

sum119897isin119871(119895)

119901119878119895119897119889119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119901119868119896119897119889119868119896119897119910119868119896119897

+ sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

119901119871119896101584011989711988911987111989610158401198971199101198711198961015840119897sum119894isin119868

sum119895isin119869

119901119894119895119889119894119895119909119894119895

+sum119895isin119869

sum119896isin119870

119901119895119896119889119895119896119909119895119896 +sum119895isin119869

sum1198961015840isin1198701015840

119901119895119896101584011988911989511989610158401199091198951198961015840

(3)

The Sustainable Waste Management Network (SWMN)design model can be formulated as a multiobjective mixed-integer program

[SWMN] min 119865119888 119865119906 119865ℎ (4)

st sum119895isin119869

119891119894119895 = 119863119894 forall119894 isin 119868 (5)

sum119894isin119868

119891119894119895 = sum119896isin119870

119891119895119896 forall119895 isin 119869 (6)

6 Journal of Advanced Transportation

sum119894isin119868

119891119894119895 le sum119897isin119871(119895)

119862119895119897119910119878119895119897 forall119895 isin 119869 (7)

sum119895isin119869

119891119895119896 le sum119897isin119871(119896)

119862119896119897119910119868119896119897 forall119896 isin 119870 (8)

sum119895isin119869

1198911198951198961015840 le sum119897isin119871(1198961015840)

11986211989610158401198971199101198711198961015840119897 forall1198961015840 isin 1198701015840 (9)

119891119894119895 le 119862119895119897119909119894119895 forall119894 isin 119868 119895 isin 119869 (10)

119891119895119896 le 119862119896119897119909119895119896 forall119895 isin 119869 119896 isin 119870 (11)

1198911198951198961015840 le 11986211989610158401198971199091198951198961015840 forall119895 isin 119869 119896 isin 119870 (12)

sum119897isin119871(119895)

119910119878119895119897 le 1 forall119895 isin 119869 (13)

sum119897isin119871(119896)

119910119868119896119897 le 1 forall119896 isin 119870 (14)

sum119897isin119871(1198961015840)

1199101198711198961015840119897 le 1 forall1198961015840 isin 1198701015840 (15)

119891119894119895 119891119895119896 1198911198951198961015840 ge 0 forall119894 119895 119896 1198961015840 (16)

119910119878119895119897 119910119868119896119897 y1198711198961015840119897 isin 0 1 forall119895 119896 1198961015840 119897 (17)

119909119894119895 119909119895119896 1199091198951198961015840 isin Z+ forall119894 119895 119896 1198961015840 (18)

The objective (4) is to minimize the costs land-use ratiosand impact of transportation Constraints (5) state that theoutflow of waste from any given collection center 119894 mustbe equal to 119863119894 Equations (6) are flow balance constraintsenforcing that the inflow at a sorting facility 119895 is entirelyforwarded to incinerators 119896 and landfills 1198961015840 Constraints (7)-(9) are the size-dependent capacity constraints at any facilityof the network Constraints (10)-(12) are the transportationcapacity limitations Inequalities (13)-(15) enforce that onlyone size can be selected if a facility is open at a given locationConstraints (16)-(18) define the decision variablesrsquo domains

34 Solution Algorithms The computational results dis-played in Section 4 are obtained from various optimizationmodels solved under single-objective functions and multiob-jective functions We refer to these models using the notationSWMN() where we define inside the brackets the objectivesbeing optimized together For example SWMN(119865119888 119865ℎ) is themultiobjective problem optimizing both costs and healthimpact whereas SWMN(119865119906) is the single-objective modelminimizing only the land-use impact Single-objective mod-els can be solved with numerical methods such as branchand boundmethod As formultiobjective models amin-maxapproach is implemented to identify solutions that minimizethe deviations from the ideal results Formally let 119865lowast119888 119865

lowast119906 and

119865lowastℎ be the optimal value obtained by solving the respectivesingle-objective problems Furthermore let 119865119898119886119909119888 119865119898119886119909119906 and119865119898119886119909ℎ upper bounds be set equal to the worst value obtainedby each function across the single-objective problemsWe can

now define the deviation levels between each objective and itsideal target by normalizing the functions as follows

120590119888 =119865119888 minus 119865lowast119888

119865119898119886119909119888 minus 119865lowast119888(19)

120590119906 =119865119906 minus 119865lowast119906119865119898119886119909119906 minus 119865lowast119906

(20)

120590ℎ =119865ℎ minus 119865lowastℎ119865119898119886119909ℎ

minus 119865lowastℎ

(21)

By adding a new continuous decision variable 119911 we canformulate a min-max goal attainment on the deviations ofthree objectives as follows

[SWMN (119865119888 119865119906 119865ℎ)] min 119911 (22)

st 120590119888 le 119911 (23)

120590119906 le 119911 (24)

120590ℎ le 119911 (25)

(5) minus (18) (26)

The objective of min-max SWMN is to minimize thelargest deviation from optimal targets across the three func-tions considered The model can be easily modified to targetonly two objectives

4 Case Study

In this section we apply the proposed SWMN model to acase study in Pathum Thani province in Thailand The wastemanagement system in Thailand is of interest as very littleplanning has been used in the past to locate waste facilitiesNowadays among a total of 2490 municipal solid wastesites only 499 (20) adopt safety standards such as sani-taryengineer landfill controlled dumping and incinerationwith air pollution-controlled system [36]The rest of the sitesimplement unhealthy practices such as open dumping andincineration without air pollution-controlled system As aconsequence the uncontrolled release of leachates and gasesfrom these dumps is frequent This is taking a toll on bothenvironment and society For example in 2010 a fire brokeout at the Phraeksa dump site causing hundreds of residentsto flee the area This incident prompted local governmentsacross Thailand to reexamine their regulatory approaches inhealth and environmental safety

PathumThani is located in the central region ofThailandwithin the Bangkok metropolitan area (Figure 3) It coversa total area of 15259 km2 organized into 7 districts 60subdistricts and 529 villages Its population has steadilyincreased in the past decade to about 12 million As a resultthe amount of waste generated increased to 0612 milliontonnesyear [36] As the province is quite vast we narrow thefocus toMuang PathumThani SamKhok and Lat LumKaeodistricts for our case study (Figure 4) Currently solid wastesfrom communities are gathered at collection centers across

Journal of Advanced Transportation 7

Table 1 Safety distance from waste facilities

Criteria Sorting facility (km) Incinerator (km) Landfill (km)Residential area 1 2 1Archaeological heritage site 1 1 1River 1 1 1Pond - 03 03Main road - 03 03

Pathum ani

Bangkok

Phra Nakhon Si Ayutthaya

Nakhon Nayok

Saraburi

Nonthaburi

Figure 3 Central Thailand

subdistricts Wastes at collection centers are transported tosorting facilities and subsequently sent to either incineratorsor landfills Recycling is purposely not included in this studyas it is currently done by private companies The validation ofthe proposed model is done by determining the location andsize of sorting and disposal facilities

41 Parameters

Land Availability Assessment and Candidate Locations Inorder to quantify the land available an initial screening isnecessary to exclude from the analysis places such as riverspondsmain roads archaeological heritage sites and residen-tial areas We further include a buffering area to guaranteesafe distances between waste sites As shown in Table 1 thesize of these buffers is set according to the regulation andguideline of MSWM developed by the Pollution ControlDepartment (PCD)

A number of polygons are identified by combiningavailable land with subdistrict boundaries Based on theirsizes these polygons are further divided and their centroidis selected as a facility location Available land for landfillsiting is shown in Figure 4 Since candidate locations ofthe three types of facilities overlap we further constrain themathematical model to avoid colocations

To ensure environmental justice across the three districtswe perform the land-use assessment at the subdistrict levelFor any location within a subdistrict we compute parameters119904119878119895119897 119904119868119896119897 and 119904

1198711198961015840119897 as the following ratio

Direct + Indirect land use with facility of size 119897Total land available in the sub-district

(27)

For each facility 3 capacity levels are considered smallmedium and large Their direct and indirect land-use areshown inTable 2The values are estimated by land occupationLCIA methodology as previously described in our land-useimpact assessment

Traveling Distances All wastes are transported from the col-lection centers to the sorting facilities using 16-tonne (light)trucks From the sorting facilities to both the incineratorand landfill sites 32-tonne (heavy) trucks are used Travelingdistances are estimated using ArcGIS and a digital map ofPathum Thani Specifically having defined the candidatelocations we use a network analysis tool to determine theshortest routes

Public Health Impact Assessment To measure the publichealth impact this study computes the DALYs for peopleaffected by the MSWM system The first step is to estimatethe number of people living near the supply chain No datais currently available showing the population distribution atthe household level ArcGIS is used to count the total numberof residential buildings surrounding the waste transportationroutes and MSWM facilities

To estimate the damage to public health caused by anMSWM system this study adopts the emission-to-exposuremodel used byGouge et al [37] andGreco et al [38]They useseveral buffer distances to estimate the health impact causedby transport pollution In our study we set the buffer distancefor transportation routes to 100m For MSWM facilities theaffected areas are assumed to increase with the waste disposaldimension Moreover due to a long history of unsanitarypractices in Thailand landfills are assumed to have a largerimpact than other MSWM facilities (Table 3)

The estimation of the number of affected people is madebased on the information of the total population living in thearea and the number of residential buildings The proposedestimation approach is expected to give a more accurateestimate of affected people than the previous approach [39]Varying impact distances corresponding to different typesand sizes of facilities are used instead of one single impactdistanceThe second step is tomultiply the number of affected

8 Journal of Advanced Transportation

Nonthaburi

Bangkok

Pathum ani

Candidate landfill siting locationsUnsuitable area for landfill siting

Figure 4 Landfill locations

Table 2 Direct and indirect land-use impacts

Direct land-use (1198982) Indirect land-use (1198982)Waste facility Small size Medium size Large size Small size Medium size Large sizeSorting facility 4800 8000 16000 6191 10780 21559Incinerator 8000 16000 24000 11971 23941 35911Landfill 80000 160000 192000 127770 255525 335295

Table 3 Facilities impact on public health

Facilities Sized Capacity (tonneday) Affected areas (km) DALYs

Sorting FacilitySmall 50 03 007

Medium 100 06 014Large 300 18 028

IncineratorSmall 50 05 595

Medium 100 1 119Large 150 15 1785

LandfillSmall 50 1 389

Medium 100 2 778Large 150 3 1166

people near the transportation routes and MSWM facilitiesby the DALYs coefficients which are summarized in Tables 3and 4 The number of DALYs is estimated based on a 30-yearoperational period using the ReCiPe 2008 Endpoint LCIAmethod [33] Only local-scale environmental impacts aretaken into account including human toxicity photochemicaloxidant formation PM formation and ionizing radiationThe damage due to climate change and ozone depletion isneglected Finally the capacity of waste sites and trucks isselected from those available in SimaPro 73 (LCA software)which covers a wide range of typical facilities and operationsThe entire dataset can be found in Kachapanya [40]

42 Results and Discussion This section presents the resultsfrom the computational analysis which is carried out on aWindows 10 machine using an Intel i7-6700HQ processorwith 8GB of RAM CPLEX 126 optimization studio is usedto solve the mathematical models The analysis is organizedin two subsections single-objective and multiobjective opti-mizations

The results are interpreted in terms of satisfaction levelsof each objective A satisfaction level of 100 indicates thatthe objective is equal to its optimal level Conversely smallersatisfaction levels indicate that there is a gap between theobjective and its best achievable target Formally these levels

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

4 Journal of Advanced Transportation

Landfills

Incinerators

Recycling by private companies

Sorting facilities

Collection centers

transport by small truck

transport by large truck

transportationcost

transportationcost

disposal

seperation

collection

Figure 2 Waste management supply chain

using the ReCiPe 2008 Endpoint LCIA method [33] Thenthe total DALYs are obtained by multiplying the individualimpact of exposure by the total number of people livingwithin the affected area

32 Land-Use Impact Assessment Processes in MSWM facil-ities including construction operation and closure normallytake place over long timescales Under traditional centralizedwaste systems the life expectancy of MSWM facilities islonger due to the need for larger-sized facilities to copewith increased waste generation in cities Communitiessurrounding waste facilities have to deal with the long-termnegative external effects of municipal solid waste Thereforethe issue of disproportionate environmental burden amongpopulation in certain areas is a pressing concern especiallyfor rapidly urbanized cities From a strategic point of viewit is important that each administrative area in a city isnot overly burdened by land-use impact or other importantenvironmental stressors caused by MSWM facilities Theprinciple of environmental justice must be adopted at theearly phase of MSWM planning

In this study the spatial planning of MSWM infrastruc-ture uses a land-use equality strategy to mitigate the impacton local land-use in areas with substantial land-use stressThe proposed planning approach involves a two-step processThe first step is to evaluate the current land availability ineach geographical or administrative area within a city This

step generally requires knowledge of land-use policies and theuse of GIS tools to screen out portions of land which are notsuitable for development The second step is to calculate theland-use stress of each administrative area which is the ratioof land-use impact caused byMSWMfacilities to the availableland In our study the level of land-use impact is calculatedbased on the total amount of direct and indirect land-useThe direct land-use is the actual land area used for facilityestablishment The indirect land-use is estimated by landoccupation LCIA methodology which assesses the impacton land quality over a given period The ReCiPe Midpoint(H) V107Europe ReCiPe H method is used in our study toaccount for the land occupation impact based on the type andcapacity of facilities Previous attempts to integrate direct andindirect land-use impacts have been made in LCA studies toaccount for the relevant land-use impacts [34 35]

33 Optimization Model for Sustainable MSWM In thissection we introduce a mathematical formulation for thesustainable MSWM problem The multiobjective mixed-integer model is a customization of the popular facilitylocation modelWe consider a 3-echelon supply chain wheresolid wastes are gathered in collection centers then movedto sorting facilities and finally sent to either incinerators orlandfills Figure 2 shows an example of this supply chain

We assume that decisions can be made on both locationsand sizes of tier 2 and tier 3 of the supply chain (ie sorting

Journal of Advanced Transportation 5

facilities and landfillsincinerators) This directly affects thecapacity of each facility its land-use and its impact onpublic health The objective is to identify locations sizesand routes to minimize costs land-use and public healthimpact Superscripts 119878 119868 and 119871 are used throughout themathematical formulation to refer to sorting incinerator andlandfill facilities respectively

The modelrsquos notation is given below

Sets and Indices

(i) 119868 is the set of collection centers indexed by 119894(ii) 119869 is the set of sorting facility locations indexed by 119895(iii) 119870 is the set of incinerator locations indexed by 119896(iv) 1198701015840 is the set of landfill locations indexed by 1198961015840(v) 119871(119895) 119871(119896) 119871(1198961015840) are the set of available sizes at loca-

tions 119895 119896 and 1198961015840 indexed by 119897

Parameters

(i) 119905119894119895 119905119895119896 1199051198951198961015840 are the transportation costs on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(ii) 119888119878119895119897 119888119868119896119897 1198881198711198961015840119897 are the fixed costs to open facilities of size 119897

(iii) 119862119878119895119897 119862119868119896119897 1198621198711198961015840119897 are the storage capacities of facilities of

size 119897(iv) 119862119894119895 119862119895119896 1198621198951198961015840 define the maximum amount of waste

that a single trip can carry over links (119894 119895) (119895 119896) and(119895 1198961015840) respectively

(v) 119900119878119895 119900119868119896 1199001198711198951198961015840 are unit operations costs tomanage the flow

of solid waste for each facility(vi) 119904119878119895119897 119904

119868119896119897 1199041198711198961015840119897 are land-use stress ratios for facilities of size

119897(vii) 119863119894 is the amount of solid waste available at collection

center 119894(viii) 119901119894119895 119901119895119896 1199011198951198961015840 are the number of people living nearby

links (119894 119895) (119895 119896) and (119895 1198961015840) respectively(ix) 119901119878119895119897 119901

119868119896119897 1199011198711198961015840119897 are the number of people living near a

facility of size 119897(x) 119889119894119895 119889119895119896 1198891198951198961015840 are the DALYs per person due to trans-

portation activities on links (119894 119895) (119895 119896) and (119895 1198961015840)respectively

(xi) 119889119878119895119897 119889119868119896119897 1198891198711198961015840119897 are the DALYs per person due to size 119897

facility operations

Decision Variables

(i) 119910119878119895119897 119910119868119896119897 1199101198711198961015840119897 are binary location variables equal to 1

when sorting facilities incinerators and landfills ofsize 119897 are open at their respective locations 119895 119896 and1198961015840

(ii) 119909119894119895 119909119895119896 1199091198951198961015840 are the number of trips on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(iii) 119891119894119895 119891119895119896 1198911198951198961015840 denote the amount of solid waste trans-ported on links (119894 119895) (119895 119896) and (119895 1198961015840) respectively

The cost function 119865119888 is computed as follows

119865119888 = sum119895isin119869

sum119897isin119871(119895)

119888119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119888119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11988811987111989610158401198971199101198711198961015840119897

+sum119894isin119868

sum119895isin119869

(119905119894119895 + 119900119878119895) 119909119894119895 +sum

119895isin119869

sum119896isin119870

(119905119895119896 + 119900119868119896) 119909119895119896

+sum119895isin119869

sum1198961015840isin1198701015840

(1199051198951198961015840 + 1199001198711198961015840) 1199091198951198961015840

(1)

The overall cost is the sum of the fixed costs to opensorting facilities incinerators and landfills plus the opera-tional costs of transporting andmanaging the solidwaste flowacross the network

A second function 119865119906 is introduced to measure theaverage land-use stress The function is formally defined asfollows

119865119906 = sum119895isin119869

sum119897isin119871(119895)

119904119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119904119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11990411987111989610158401198971199101198711198961015840119897 (2)

The function is the sum of all the land-use ratio acrossall candidate locations Parameters 119904119895119897 119904119896119897 1199041198961015840119897 represent theratios for land used and land available This ratio can becomputed by looking at the entire network or by narrowingdown the focus to smaller districts to compute the impact ofland-use at a local level

Finally a third function 119865ℎ is used to evaluate the impactof transportation and facilities on the populationrsquos health Thefunction is defined as follows

119865ℎ = sum119895isin119869

sum119897isin119871(119895)

119901119878119895119897119889119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119901119868119896119897119889119868119896119897119910119868119896119897

+ sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

119901119871119896101584011989711988911987111989610158401198971199101198711198961015840119897sum119894isin119868

sum119895isin119869

119901119894119895119889119894119895119909119894119895

+sum119895isin119869

sum119896isin119870

119901119895119896119889119895119896119909119895119896 +sum119895isin119869

sum1198961015840isin1198701015840

119901119895119896101584011988911989511989610158401199091198951198961015840

(3)

The Sustainable Waste Management Network (SWMN)design model can be formulated as a multiobjective mixed-integer program

[SWMN] min 119865119888 119865119906 119865ℎ (4)

st sum119895isin119869

119891119894119895 = 119863119894 forall119894 isin 119868 (5)

sum119894isin119868

119891119894119895 = sum119896isin119870

119891119895119896 forall119895 isin 119869 (6)

6 Journal of Advanced Transportation

sum119894isin119868

119891119894119895 le sum119897isin119871(119895)

119862119895119897119910119878119895119897 forall119895 isin 119869 (7)

sum119895isin119869

119891119895119896 le sum119897isin119871(119896)

119862119896119897119910119868119896119897 forall119896 isin 119870 (8)

sum119895isin119869

1198911198951198961015840 le sum119897isin119871(1198961015840)

11986211989610158401198971199101198711198961015840119897 forall1198961015840 isin 1198701015840 (9)

119891119894119895 le 119862119895119897119909119894119895 forall119894 isin 119868 119895 isin 119869 (10)

119891119895119896 le 119862119896119897119909119895119896 forall119895 isin 119869 119896 isin 119870 (11)

1198911198951198961015840 le 11986211989610158401198971199091198951198961015840 forall119895 isin 119869 119896 isin 119870 (12)

sum119897isin119871(119895)

119910119878119895119897 le 1 forall119895 isin 119869 (13)

sum119897isin119871(119896)

119910119868119896119897 le 1 forall119896 isin 119870 (14)

sum119897isin119871(1198961015840)

1199101198711198961015840119897 le 1 forall1198961015840 isin 1198701015840 (15)

119891119894119895 119891119895119896 1198911198951198961015840 ge 0 forall119894 119895 119896 1198961015840 (16)

119910119878119895119897 119910119868119896119897 y1198711198961015840119897 isin 0 1 forall119895 119896 1198961015840 119897 (17)

119909119894119895 119909119895119896 1199091198951198961015840 isin Z+ forall119894 119895 119896 1198961015840 (18)

The objective (4) is to minimize the costs land-use ratiosand impact of transportation Constraints (5) state that theoutflow of waste from any given collection center 119894 mustbe equal to 119863119894 Equations (6) are flow balance constraintsenforcing that the inflow at a sorting facility 119895 is entirelyforwarded to incinerators 119896 and landfills 1198961015840 Constraints (7)-(9) are the size-dependent capacity constraints at any facilityof the network Constraints (10)-(12) are the transportationcapacity limitations Inequalities (13)-(15) enforce that onlyone size can be selected if a facility is open at a given locationConstraints (16)-(18) define the decision variablesrsquo domains

34 Solution Algorithms The computational results dis-played in Section 4 are obtained from various optimizationmodels solved under single-objective functions and multiob-jective functions We refer to these models using the notationSWMN() where we define inside the brackets the objectivesbeing optimized together For example SWMN(119865119888 119865ℎ) is themultiobjective problem optimizing both costs and healthimpact whereas SWMN(119865119906) is the single-objective modelminimizing only the land-use impact Single-objective mod-els can be solved with numerical methods such as branchand boundmethod As formultiobjective models amin-maxapproach is implemented to identify solutions that minimizethe deviations from the ideal results Formally let 119865lowast119888 119865

lowast119906 and

119865lowastℎ be the optimal value obtained by solving the respectivesingle-objective problems Furthermore let 119865119898119886119909119888 119865119898119886119909119906 and119865119898119886119909ℎ upper bounds be set equal to the worst value obtainedby each function across the single-objective problemsWe can

now define the deviation levels between each objective and itsideal target by normalizing the functions as follows

120590119888 =119865119888 minus 119865lowast119888

119865119898119886119909119888 minus 119865lowast119888(19)

120590119906 =119865119906 minus 119865lowast119906119865119898119886119909119906 minus 119865lowast119906

(20)

120590ℎ =119865ℎ minus 119865lowastℎ119865119898119886119909ℎ

minus 119865lowastℎ

(21)

By adding a new continuous decision variable 119911 we canformulate a min-max goal attainment on the deviations ofthree objectives as follows

[SWMN (119865119888 119865119906 119865ℎ)] min 119911 (22)

st 120590119888 le 119911 (23)

120590119906 le 119911 (24)

120590ℎ le 119911 (25)

(5) minus (18) (26)

The objective of min-max SWMN is to minimize thelargest deviation from optimal targets across the three func-tions considered The model can be easily modified to targetonly two objectives

4 Case Study

In this section we apply the proposed SWMN model to acase study in Pathum Thani province in Thailand The wastemanagement system in Thailand is of interest as very littleplanning has been used in the past to locate waste facilitiesNowadays among a total of 2490 municipal solid wastesites only 499 (20) adopt safety standards such as sani-taryengineer landfill controlled dumping and incinerationwith air pollution-controlled system [36]The rest of the sitesimplement unhealthy practices such as open dumping andincineration without air pollution-controlled system As aconsequence the uncontrolled release of leachates and gasesfrom these dumps is frequent This is taking a toll on bothenvironment and society For example in 2010 a fire brokeout at the Phraeksa dump site causing hundreds of residentsto flee the area This incident prompted local governmentsacross Thailand to reexamine their regulatory approaches inhealth and environmental safety

PathumThani is located in the central region ofThailandwithin the Bangkok metropolitan area (Figure 3) It coversa total area of 15259 km2 organized into 7 districts 60subdistricts and 529 villages Its population has steadilyincreased in the past decade to about 12 million As a resultthe amount of waste generated increased to 0612 milliontonnesyear [36] As the province is quite vast we narrow thefocus toMuang PathumThani SamKhok and Lat LumKaeodistricts for our case study (Figure 4) Currently solid wastesfrom communities are gathered at collection centers across

Journal of Advanced Transportation 7

Table 1 Safety distance from waste facilities

Criteria Sorting facility (km) Incinerator (km) Landfill (km)Residential area 1 2 1Archaeological heritage site 1 1 1River 1 1 1Pond - 03 03Main road - 03 03

Pathum ani

Bangkok

Phra Nakhon Si Ayutthaya

Nakhon Nayok

Saraburi

Nonthaburi

Figure 3 Central Thailand

subdistricts Wastes at collection centers are transported tosorting facilities and subsequently sent to either incineratorsor landfills Recycling is purposely not included in this studyas it is currently done by private companies The validation ofthe proposed model is done by determining the location andsize of sorting and disposal facilities

41 Parameters

Land Availability Assessment and Candidate Locations Inorder to quantify the land available an initial screening isnecessary to exclude from the analysis places such as riverspondsmain roads archaeological heritage sites and residen-tial areas We further include a buffering area to guaranteesafe distances between waste sites As shown in Table 1 thesize of these buffers is set according to the regulation andguideline of MSWM developed by the Pollution ControlDepartment (PCD)

A number of polygons are identified by combiningavailable land with subdistrict boundaries Based on theirsizes these polygons are further divided and their centroidis selected as a facility location Available land for landfillsiting is shown in Figure 4 Since candidate locations ofthe three types of facilities overlap we further constrain themathematical model to avoid colocations

To ensure environmental justice across the three districtswe perform the land-use assessment at the subdistrict levelFor any location within a subdistrict we compute parameters119904119878119895119897 119904119868119896119897 and 119904

1198711198961015840119897 as the following ratio

Direct + Indirect land use with facility of size 119897Total land available in the sub-district

(27)

For each facility 3 capacity levels are considered smallmedium and large Their direct and indirect land-use areshown inTable 2The values are estimated by land occupationLCIA methodology as previously described in our land-useimpact assessment

Traveling Distances All wastes are transported from the col-lection centers to the sorting facilities using 16-tonne (light)trucks From the sorting facilities to both the incineratorand landfill sites 32-tonne (heavy) trucks are used Travelingdistances are estimated using ArcGIS and a digital map ofPathum Thani Specifically having defined the candidatelocations we use a network analysis tool to determine theshortest routes

Public Health Impact Assessment To measure the publichealth impact this study computes the DALYs for peopleaffected by the MSWM system The first step is to estimatethe number of people living near the supply chain No datais currently available showing the population distribution atthe household level ArcGIS is used to count the total numberof residential buildings surrounding the waste transportationroutes and MSWM facilities

To estimate the damage to public health caused by anMSWM system this study adopts the emission-to-exposuremodel used byGouge et al [37] andGreco et al [38]They useseveral buffer distances to estimate the health impact causedby transport pollution In our study we set the buffer distancefor transportation routes to 100m For MSWM facilities theaffected areas are assumed to increase with the waste disposaldimension Moreover due to a long history of unsanitarypractices in Thailand landfills are assumed to have a largerimpact than other MSWM facilities (Table 3)

The estimation of the number of affected people is madebased on the information of the total population living in thearea and the number of residential buildings The proposedestimation approach is expected to give a more accurateestimate of affected people than the previous approach [39]Varying impact distances corresponding to different typesand sizes of facilities are used instead of one single impactdistanceThe second step is tomultiply the number of affected

8 Journal of Advanced Transportation

Nonthaburi

Bangkok

Pathum ani

Candidate landfill siting locationsUnsuitable area for landfill siting

Figure 4 Landfill locations

Table 2 Direct and indirect land-use impacts

Direct land-use (1198982) Indirect land-use (1198982)Waste facility Small size Medium size Large size Small size Medium size Large sizeSorting facility 4800 8000 16000 6191 10780 21559Incinerator 8000 16000 24000 11971 23941 35911Landfill 80000 160000 192000 127770 255525 335295

Table 3 Facilities impact on public health

Facilities Sized Capacity (tonneday) Affected areas (km) DALYs

Sorting FacilitySmall 50 03 007

Medium 100 06 014Large 300 18 028

IncineratorSmall 50 05 595

Medium 100 1 119Large 150 15 1785

LandfillSmall 50 1 389

Medium 100 2 778Large 150 3 1166

people near the transportation routes and MSWM facilitiesby the DALYs coefficients which are summarized in Tables 3and 4 The number of DALYs is estimated based on a 30-yearoperational period using the ReCiPe 2008 Endpoint LCIAmethod [33] Only local-scale environmental impacts aretaken into account including human toxicity photochemicaloxidant formation PM formation and ionizing radiationThe damage due to climate change and ozone depletion isneglected Finally the capacity of waste sites and trucks isselected from those available in SimaPro 73 (LCA software)which covers a wide range of typical facilities and operationsThe entire dataset can be found in Kachapanya [40]

42 Results and Discussion This section presents the resultsfrom the computational analysis which is carried out on aWindows 10 machine using an Intel i7-6700HQ processorwith 8GB of RAM CPLEX 126 optimization studio is usedto solve the mathematical models The analysis is organizedin two subsections single-objective and multiobjective opti-mizations

The results are interpreted in terms of satisfaction levelsof each objective A satisfaction level of 100 indicates thatthe objective is equal to its optimal level Conversely smallersatisfaction levels indicate that there is a gap between theobjective and its best achievable target Formally these levels

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

Journal of Advanced Transportation 5

facilities and landfillsincinerators) This directly affects thecapacity of each facility its land-use and its impact onpublic health The objective is to identify locations sizesand routes to minimize costs land-use and public healthimpact Superscripts 119878 119868 and 119871 are used throughout themathematical formulation to refer to sorting incinerator andlandfill facilities respectively

The modelrsquos notation is given below

Sets and Indices

(i) 119868 is the set of collection centers indexed by 119894(ii) 119869 is the set of sorting facility locations indexed by 119895(iii) 119870 is the set of incinerator locations indexed by 119896(iv) 1198701015840 is the set of landfill locations indexed by 1198961015840(v) 119871(119895) 119871(119896) 119871(1198961015840) are the set of available sizes at loca-

tions 119895 119896 and 1198961015840 indexed by 119897

Parameters

(i) 119905119894119895 119905119895119896 1199051198951198961015840 are the transportation costs on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(ii) 119888119878119895119897 119888119868119896119897 1198881198711198961015840119897 are the fixed costs to open facilities of size 119897

(iii) 119862119878119895119897 119862119868119896119897 1198621198711198961015840119897 are the storage capacities of facilities of

size 119897(iv) 119862119894119895 119862119895119896 1198621198951198961015840 define the maximum amount of waste

that a single trip can carry over links (119894 119895) (119895 119896) and(119895 1198961015840) respectively

(v) 119900119878119895 119900119868119896 1199001198711198951198961015840 are unit operations costs tomanage the flow

of solid waste for each facility(vi) 119904119878119895119897 119904

119868119896119897 1199041198711198961015840119897 are land-use stress ratios for facilities of size

119897(vii) 119863119894 is the amount of solid waste available at collection

center 119894(viii) 119901119894119895 119901119895119896 1199011198951198961015840 are the number of people living nearby

links (119894 119895) (119895 119896) and (119895 1198961015840) respectively(ix) 119901119878119895119897 119901

119868119896119897 1199011198711198961015840119897 are the number of people living near a

facility of size 119897(x) 119889119894119895 119889119895119896 1198891198951198961015840 are the DALYs per person due to trans-

portation activities on links (119894 119895) (119895 119896) and (119895 1198961015840)respectively

(xi) 119889119878119895119897 119889119868119896119897 1198891198711198961015840119897 are the DALYs per person due to size 119897

facility operations

Decision Variables

(i) 119910119878119895119897 119910119868119896119897 1199101198711198961015840119897 are binary location variables equal to 1

when sorting facilities incinerators and landfills ofsize 119897 are open at their respective locations 119895 119896 and1198961015840

(ii) 119909119894119895 119909119895119896 1199091198951198961015840 are the number of trips on links(119894 119895) (119895 119896) and (119895 1198961015840) respectively

(iii) 119891119894119895 119891119895119896 1198911198951198961015840 denote the amount of solid waste trans-ported on links (119894 119895) (119895 119896) and (119895 1198961015840) respectively

The cost function 119865119888 is computed as follows

119865119888 = sum119895isin119869

sum119897isin119871(119895)

119888119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119888119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11988811987111989610158401198971199101198711198961015840119897

+sum119894isin119868

sum119895isin119869

(119905119894119895 + 119900119878119895) 119909119894119895 +sum

119895isin119869

sum119896isin119870

(119905119895119896 + 119900119868119896) 119909119895119896

+sum119895isin119869

sum1198961015840isin1198701015840

(1199051198951198961015840 + 1199001198711198961015840) 1199091198951198961015840

(1)

The overall cost is the sum of the fixed costs to opensorting facilities incinerators and landfills plus the opera-tional costs of transporting andmanaging the solidwaste flowacross the network

A second function 119865119906 is introduced to measure theaverage land-use stress The function is formally defined asfollows

119865119906 = sum119895isin119869

sum119897isin119871(119895)

119904119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119904119868119896119897119910119868119896119897 + sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

11990411987111989610158401198971199101198711198961015840119897 (2)

The function is the sum of all the land-use ratio acrossall candidate locations Parameters 119904119895119897 119904119896119897 1199041198961015840119897 represent theratios for land used and land available This ratio can becomputed by looking at the entire network or by narrowingdown the focus to smaller districts to compute the impact ofland-use at a local level

Finally a third function 119865ℎ is used to evaluate the impactof transportation and facilities on the populationrsquos health Thefunction is defined as follows

119865ℎ = sum119895isin119869

sum119897isin119871(119895)

119901119878119895119897119889119878119895119897119910119878119895119897 + sum119896isin119870

sum119897isin119871(119896)

119901119868119896119897119889119868119896119897119910119868119896119897

+ sum1198961015840isin1198701015840

sum119897isin119871(1198961015840)

119901119871119896101584011989711988911987111989610158401198971199101198711198961015840119897sum119894isin119868

sum119895isin119869

119901119894119895119889119894119895119909119894119895

+sum119895isin119869

sum119896isin119870

119901119895119896119889119895119896119909119895119896 +sum119895isin119869

sum1198961015840isin1198701015840

119901119895119896101584011988911989511989610158401199091198951198961015840

(3)

The Sustainable Waste Management Network (SWMN)design model can be formulated as a multiobjective mixed-integer program

[SWMN] min 119865119888 119865119906 119865ℎ (4)

st sum119895isin119869

119891119894119895 = 119863119894 forall119894 isin 119868 (5)

sum119894isin119868

119891119894119895 = sum119896isin119870

119891119895119896 forall119895 isin 119869 (6)

6 Journal of Advanced Transportation

sum119894isin119868

119891119894119895 le sum119897isin119871(119895)

119862119895119897119910119878119895119897 forall119895 isin 119869 (7)

sum119895isin119869

119891119895119896 le sum119897isin119871(119896)

119862119896119897119910119868119896119897 forall119896 isin 119870 (8)

sum119895isin119869

1198911198951198961015840 le sum119897isin119871(1198961015840)

11986211989610158401198971199101198711198961015840119897 forall1198961015840 isin 1198701015840 (9)

119891119894119895 le 119862119895119897119909119894119895 forall119894 isin 119868 119895 isin 119869 (10)

119891119895119896 le 119862119896119897119909119895119896 forall119895 isin 119869 119896 isin 119870 (11)

1198911198951198961015840 le 11986211989610158401198971199091198951198961015840 forall119895 isin 119869 119896 isin 119870 (12)

sum119897isin119871(119895)

119910119878119895119897 le 1 forall119895 isin 119869 (13)

sum119897isin119871(119896)

119910119868119896119897 le 1 forall119896 isin 119870 (14)

sum119897isin119871(1198961015840)

1199101198711198961015840119897 le 1 forall1198961015840 isin 1198701015840 (15)

119891119894119895 119891119895119896 1198911198951198961015840 ge 0 forall119894 119895 119896 1198961015840 (16)

119910119878119895119897 119910119868119896119897 y1198711198961015840119897 isin 0 1 forall119895 119896 1198961015840 119897 (17)

119909119894119895 119909119895119896 1199091198951198961015840 isin Z+ forall119894 119895 119896 1198961015840 (18)

The objective (4) is to minimize the costs land-use ratiosand impact of transportation Constraints (5) state that theoutflow of waste from any given collection center 119894 mustbe equal to 119863119894 Equations (6) are flow balance constraintsenforcing that the inflow at a sorting facility 119895 is entirelyforwarded to incinerators 119896 and landfills 1198961015840 Constraints (7)-(9) are the size-dependent capacity constraints at any facilityof the network Constraints (10)-(12) are the transportationcapacity limitations Inequalities (13)-(15) enforce that onlyone size can be selected if a facility is open at a given locationConstraints (16)-(18) define the decision variablesrsquo domains

34 Solution Algorithms The computational results dis-played in Section 4 are obtained from various optimizationmodels solved under single-objective functions and multiob-jective functions We refer to these models using the notationSWMN() where we define inside the brackets the objectivesbeing optimized together For example SWMN(119865119888 119865ℎ) is themultiobjective problem optimizing both costs and healthimpact whereas SWMN(119865119906) is the single-objective modelminimizing only the land-use impact Single-objective mod-els can be solved with numerical methods such as branchand boundmethod As formultiobjective models amin-maxapproach is implemented to identify solutions that minimizethe deviations from the ideal results Formally let 119865lowast119888 119865

lowast119906 and

119865lowastℎ be the optimal value obtained by solving the respectivesingle-objective problems Furthermore let 119865119898119886119909119888 119865119898119886119909119906 and119865119898119886119909ℎ upper bounds be set equal to the worst value obtainedby each function across the single-objective problemsWe can

now define the deviation levels between each objective and itsideal target by normalizing the functions as follows

120590119888 =119865119888 minus 119865lowast119888

119865119898119886119909119888 minus 119865lowast119888(19)

120590119906 =119865119906 minus 119865lowast119906119865119898119886119909119906 minus 119865lowast119906

(20)

120590ℎ =119865ℎ minus 119865lowastℎ119865119898119886119909ℎ

minus 119865lowastℎ

(21)

By adding a new continuous decision variable 119911 we canformulate a min-max goal attainment on the deviations ofthree objectives as follows

[SWMN (119865119888 119865119906 119865ℎ)] min 119911 (22)

st 120590119888 le 119911 (23)

120590119906 le 119911 (24)

120590ℎ le 119911 (25)

(5) minus (18) (26)

The objective of min-max SWMN is to minimize thelargest deviation from optimal targets across the three func-tions considered The model can be easily modified to targetonly two objectives

4 Case Study

In this section we apply the proposed SWMN model to acase study in Pathum Thani province in Thailand The wastemanagement system in Thailand is of interest as very littleplanning has been used in the past to locate waste facilitiesNowadays among a total of 2490 municipal solid wastesites only 499 (20) adopt safety standards such as sani-taryengineer landfill controlled dumping and incinerationwith air pollution-controlled system [36]The rest of the sitesimplement unhealthy practices such as open dumping andincineration without air pollution-controlled system As aconsequence the uncontrolled release of leachates and gasesfrom these dumps is frequent This is taking a toll on bothenvironment and society For example in 2010 a fire brokeout at the Phraeksa dump site causing hundreds of residentsto flee the area This incident prompted local governmentsacross Thailand to reexamine their regulatory approaches inhealth and environmental safety

PathumThani is located in the central region ofThailandwithin the Bangkok metropolitan area (Figure 3) It coversa total area of 15259 km2 organized into 7 districts 60subdistricts and 529 villages Its population has steadilyincreased in the past decade to about 12 million As a resultthe amount of waste generated increased to 0612 milliontonnesyear [36] As the province is quite vast we narrow thefocus toMuang PathumThani SamKhok and Lat LumKaeodistricts for our case study (Figure 4) Currently solid wastesfrom communities are gathered at collection centers across

Journal of Advanced Transportation 7

Table 1 Safety distance from waste facilities

Criteria Sorting facility (km) Incinerator (km) Landfill (km)Residential area 1 2 1Archaeological heritage site 1 1 1River 1 1 1Pond - 03 03Main road - 03 03

Pathum ani

Bangkok

Phra Nakhon Si Ayutthaya

Nakhon Nayok

Saraburi

Nonthaburi

Figure 3 Central Thailand

subdistricts Wastes at collection centers are transported tosorting facilities and subsequently sent to either incineratorsor landfills Recycling is purposely not included in this studyas it is currently done by private companies The validation ofthe proposed model is done by determining the location andsize of sorting and disposal facilities

41 Parameters

Land Availability Assessment and Candidate Locations Inorder to quantify the land available an initial screening isnecessary to exclude from the analysis places such as riverspondsmain roads archaeological heritage sites and residen-tial areas We further include a buffering area to guaranteesafe distances between waste sites As shown in Table 1 thesize of these buffers is set according to the regulation andguideline of MSWM developed by the Pollution ControlDepartment (PCD)

A number of polygons are identified by combiningavailable land with subdistrict boundaries Based on theirsizes these polygons are further divided and their centroidis selected as a facility location Available land for landfillsiting is shown in Figure 4 Since candidate locations ofthe three types of facilities overlap we further constrain themathematical model to avoid colocations

To ensure environmental justice across the three districtswe perform the land-use assessment at the subdistrict levelFor any location within a subdistrict we compute parameters119904119878119895119897 119904119868119896119897 and 119904

1198711198961015840119897 as the following ratio

Direct + Indirect land use with facility of size 119897Total land available in the sub-district

(27)

For each facility 3 capacity levels are considered smallmedium and large Their direct and indirect land-use areshown inTable 2The values are estimated by land occupationLCIA methodology as previously described in our land-useimpact assessment

Traveling Distances All wastes are transported from the col-lection centers to the sorting facilities using 16-tonne (light)trucks From the sorting facilities to both the incineratorand landfill sites 32-tonne (heavy) trucks are used Travelingdistances are estimated using ArcGIS and a digital map ofPathum Thani Specifically having defined the candidatelocations we use a network analysis tool to determine theshortest routes

Public Health Impact Assessment To measure the publichealth impact this study computes the DALYs for peopleaffected by the MSWM system The first step is to estimatethe number of people living near the supply chain No datais currently available showing the population distribution atthe household level ArcGIS is used to count the total numberof residential buildings surrounding the waste transportationroutes and MSWM facilities

To estimate the damage to public health caused by anMSWM system this study adopts the emission-to-exposuremodel used byGouge et al [37] andGreco et al [38]They useseveral buffer distances to estimate the health impact causedby transport pollution In our study we set the buffer distancefor transportation routes to 100m For MSWM facilities theaffected areas are assumed to increase with the waste disposaldimension Moreover due to a long history of unsanitarypractices in Thailand landfills are assumed to have a largerimpact than other MSWM facilities (Table 3)

The estimation of the number of affected people is madebased on the information of the total population living in thearea and the number of residential buildings The proposedestimation approach is expected to give a more accurateestimate of affected people than the previous approach [39]Varying impact distances corresponding to different typesand sizes of facilities are used instead of one single impactdistanceThe second step is tomultiply the number of affected

8 Journal of Advanced Transportation

Nonthaburi

Bangkok

Pathum ani

Candidate landfill siting locationsUnsuitable area for landfill siting

Figure 4 Landfill locations

Table 2 Direct and indirect land-use impacts

Direct land-use (1198982) Indirect land-use (1198982)Waste facility Small size Medium size Large size Small size Medium size Large sizeSorting facility 4800 8000 16000 6191 10780 21559Incinerator 8000 16000 24000 11971 23941 35911Landfill 80000 160000 192000 127770 255525 335295

Table 3 Facilities impact on public health

Facilities Sized Capacity (tonneday) Affected areas (km) DALYs

Sorting FacilitySmall 50 03 007

Medium 100 06 014Large 300 18 028

IncineratorSmall 50 05 595

Medium 100 1 119Large 150 15 1785

LandfillSmall 50 1 389

Medium 100 2 778Large 150 3 1166

people near the transportation routes and MSWM facilitiesby the DALYs coefficients which are summarized in Tables 3and 4 The number of DALYs is estimated based on a 30-yearoperational period using the ReCiPe 2008 Endpoint LCIAmethod [33] Only local-scale environmental impacts aretaken into account including human toxicity photochemicaloxidant formation PM formation and ionizing radiationThe damage due to climate change and ozone depletion isneglected Finally the capacity of waste sites and trucks isselected from those available in SimaPro 73 (LCA software)which covers a wide range of typical facilities and operationsThe entire dataset can be found in Kachapanya [40]

42 Results and Discussion This section presents the resultsfrom the computational analysis which is carried out on aWindows 10 machine using an Intel i7-6700HQ processorwith 8GB of RAM CPLEX 126 optimization studio is usedto solve the mathematical models The analysis is organizedin two subsections single-objective and multiobjective opti-mizations

The results are interpreted in terms of satisfaction levelsof each objective A satisfaction level of 100 indicates thatthe objective is equal to its optimal level Conversely smallersatisfaction levels indicate that there is a gap between theobjective and its best achievable target Formally these levels

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

6 Journal of Advanced Transportation

sum119894isin119868

119891119894119895 le sum119897isin119871(119895)

119862119895119897119910119878119895119897 forall119895 isin 119869 (7)

sum119895isin119869

119891119895119896 le sum119897isin119871(119896)

119862119896119897119910119868119896119897 forall119896 isin 119870 (8)

sum119895isin119869

1198911198951198961015840 le sum119897isin119871(1198961015840)

11986211989610158401198971199101198711198961015840119897 forall1198961015840 isin 1198701015840 (9)

119891119894119895 le 119862119895119897119909119894119895 forall119894 isin 119868 119895 isin 119869 (10)

119891119895119896 le 119862119896119897119909119895119896 forall119895 isin 119869 119896 isin 119870 (11)

1198911198951198961015840 le 11986211989610158401198971199091198951198961015840 forall119895 isin 119869 119896 isin 119870 (12)

sum119897isin119871(119895)

119910119878119895119897 le 1 forall119895 isin 119869 (13)

sum119897isin119871(119896)

119910119868119896119897 le 1 forall119896 isin 119870 (14)

sum119897isin119871(1198961015840)

1199101198711198961015840119897 le 1 forall1198961015840 isin 1198701015840 (15)

119891119894119895 119891119895119896 1198911198951198961015840 ge 0 forall119894 119895 119896 1198961015840 (16)

119910119878119895119897 119910119868119896119897 y1198711198961015840119897 isin 0 1 forall119895 119896 1198961015840 119897 (17)

119909119894119895 119909119895119896 1199091198951198961015840 isin Z+ forall119894 119895 119896 1198961015840 (18)

The objective (4) is to minimize the costs land-use ratiosand impact of transportation Constraints (5) state that theoutflow of waste from any given collection center 119894 mustbe equal to 119863119894 Equations (6) are flow balance constraintsenforcing that the inflow at a sorting facility 119895 is entirelyforwarded to incinerators 119896 and landfills 1198961015840 Constraints (7)-(9) are the size-dependent capacity constraints at any facilityof the network Constraints (10)-(12) are the transportationcapacity limitations Inequalities (13)-(15) enforce that onlyone size can be selected if a facility is open at a given locationConstraints (16)-(18) define the decision variablesrsquo domains

34 Solution Algorithms The computational results dis-played in Section 4 are obtained from various optimizationmodels solved under single-objective functions and multiob-jective functions We refer to these models using the notationSWMN() where we define inside the brackets the objectivesbeing optimized together For example SWMN(119865119888 119865ℎ) is themultiobjective problem optimizing both costs and healthimpact whereas SWMN(119865119906) is the single-objective modelminimizing only the land-use impact Single-objective mod-els can be solved with numerical methods such as branchand boundmethod As formultiobjective models amin-maxapproach is implemented to identify solutions that minimizethe deviations from the ideal results Formally let 119865lowast119888 119865

lowast119906 and

119865lowastℎ be the optimal value obtained by solving the respectivesingle-objective problems Furthermore let 119865119898119886119909119888 119865119898119886119909119906 and119865119898119886119909ℎ upper bounds be set equal to the worst value obtainedby each function across the single-objective problemsWe can

now define the deviation levels between each objective and itsideal target by normalizing the functions as follows

120590119888 =119865119888 minus 119865lowast119888

119865119898119886119909119888 minus 119865lowast119888(19)

120590119906 =119865119906 minus 119865lowast119906119865119898119886119909119906 minus 119865lowast119906

(20)

120590ℎ =119865ℎ minus 119865lowastℎ119865119898119886119909ℎ

minus 119865lowastℎ

(21)

By adding a new continuous decision variable 119911 we canformulate a min-max goal attainment on the deviations ofthree objectives as follows

[SWMN (119865119888 119865119906 119865ℎ)] min 119911 (22)

st 120590119888 le 119911 (23)

120590119906 le 119911 (24)

120590ℎ le 119911 (25)

(5) minus (18) (26)

The objective of min-max SWMN is to minimize thelargest deviation from optimal targets across the three func-tions considered The model can be easily modified to targetonly two objectives

4 Case Study

In this section we apply the proposed SWMN model to acase study in Pathum Thani province in Thailand The wastemanagement system in Thailand is of interest as very littleplanning has been used in the past to locate waste facilitiesNowadays among a total of 2490 municipal solid wastesites only 499 (20) adopt safety standards such as sani-taryengineer landfill controlled dumping and incinerationwith air pollution-controlled system [36]The rest of the sitesimplement unhealthy practices such as open dumping andincineration without air pollution-controlled system As aconsequence the uncontrolled release of leachates and gasesfrom these dumps is frequent This is taking a toll on bothenvironment and society For example in 2010 a fire brokeout at the Phraeksa dump site causing hundreds of residentsto flee the area This incident prompted local governmentsacross Thailand to reexamine their regulatory approaches inhealth and environmental safety

PathumThani is located in the central region ofThailandwithin the Bangkok metropolitan area (Figure 3) It coversa total area of 15259 km2 organized into 7 districts 60subdistricts and 529 villages Its population has steadilyincreased in the past decade to about 12 million As a resultthe amount of waste generated increased to 0612 milliontonnesyear [36] As the province is quite vast we narrow thefocus toMuang PathumThani SamKhok and Lat LumKaeodistricts for our case study (Figure 4) Currently solid wastesfrom communities are gathered at collection centers across

Journal of Advanced Transportation 7

Table 1 Safety distance from waste facilities

Criteria Sorting facility (km) Incinerator (km) Landfill (km)Residential area 1 2 1Archaeological heritage site 1 1 1River 1 1 1Pond - 03 03Main road - 03 03

Pathum ani

Bangkok

Phra Nakhon Si Ayutthaya

Nakhon Nayok

Saraburi

Nonthaburi

Figure 3 Central Thailand

subdistricts Wastes at collection centers are transported tosorting facilities and subsequently sent to either incineratorsor landfills Recycling is purposely not included in this studyas it is currently done by private companies The validation ofthe proposed model is done by determining the location andsize of sorting and disposal facilities

41 Parameters

Land Availability Assessment and Candidate Locations Inorder to quantify the land available an initial screening isnecessary to exclude from the analysis places such as riverspondsmain roads archaeological heritage sites and residen-tial areas We further include a buffering area to guaranteesafe distances between waste sites As shown in Table 1 thesize of these buffers is set according to the regulation andguideline of MSWM developed by the Pollution ControlDepartment (PCD)

A number of polygons are identified by combiningavailable land with subdistrict boundaries Based on theirsizes these polygons are further divided and their centroidis selected as a facility location Available land for landfillsiting is shown in Figure 4 Since candidate locations ofthe three types of facilities overlap we further constrain themathematical model to avoid colocations

To ensure environmental justice across the three districtswe perform the land-use assessment at the subdistrict levelFor any location within a subdistrict we compute parameters119904119878119895119897 119904119868119896119897 and 119904

1198711198961015840119897 as the following ratio

Direct + Indirect land use with facility of size 119897Total land available in the sub-district

(27)

For each facility 3 capacity levels are considered smallmedium and large Their direct and indirect land-use areshown inTable 2The values are estimated by land occupationLCIA methodology as previously described in our land-useimpact assessment

Traveling Distances All wastes are transported from the col-lection centers to the sorting facilities using 16-tonne (light)trucks From the sorting facilities to both the incineratorand landfill sites 32-tonne (heavy) trucks are used Travelingdistances are estimated using ArcGIS and a digital map ofPathum Thani Specifically having defined the candidatelocations we use a network analysis tool to determine theshortest routes

Public Health Impact Assessment To measure the publichealth impact this study computes the DALYs for peopleaffected by the MSWM system The first step is to estimatethe number of people living near the supply chain No datais currently available showing the population distribution atthe household level ArcGIS is used to count the total numberof residential buildings surrounding the waste transportationroutes and MSWM facilities

To estimate the damage to public health caused by anMSWM system this study adopts the emission-to-exposuremodel used byGouge et al [37] andGreco et al [38]They useseveral buffer distances to estimate the health impact causedby transport pollution In our study we set the buffer distancefor transportation routes to 100m For MSWM facilities theaffected areas are assumed to increase with the waste disposaldimension Moreover due to a long history of unsanitarypractices in Thailand landfills are assumed to have a largerimpact than other MSWM facilities (Table 3)

The estimation of the number of affected people is madebased on the information of the total population living in thearea and the number of residential buildings The proposedestimation approach is expected to give a more accurateestimate of affected people than the previous approach [39]Varying impact distances corresponding to different typesand sizes of facilities are used instead of one single impactdistanceThe second step is tomultiply the number of affected

8 Journal of Advanced Transportation

Nonthaburi

Bangkok

Pathum ani

Candidate landfill siting locationsUnsuitable area for landfill siting

Figure 4 Landfill locations

Table 2 Direct and indirect land-use impacts

Direct land-use (1198982) Indirect land-use (1198982)Waste facility Small size Medium size Large size Small size Medium size Large sizeSorting facility 4800 8000 16000 6191 10780 21559Incinerator 8000 16000 24000 11971 23941 35911Landfill 80000 160000 192000 127770 255525 335295

Table 3 Facilities impact on public health

Facilities Sized Capacity (tonneday) Affected areas (km) DALYs

Sorting FacilitySmall 50 03 007

Medium 100 06 014Large 300 18 028

IncineratorSmall 50 05 595

Medium 100 1 119Large 150 15 1785

LandfillSmall 50 1 389

Medium 100 2 778Large 150 3 1166

people near the transportation routes and MSWM facilitiesby the DALYs coefficients which are summarized in Tables 3and 4 The number of DALYs is estimated based on a 30-yearoperational period using the ReCiPe 2008 Endpoint LCIAmethod [33] Only local-scale environmental impacts aretaken into account including human toxicity photochemicaloxidant formation PM formation and ionizing radiationThe damage due to climate change and ozone depletion isneglected Finally the capacity of waste sites and trucks isselected from those available in SimaPro 73 (LCA software)which covers a wide range of typical facilities and operationsThe entire dataset can be found in Kachapanya [40]

42 Results and Discussion This section presents the resultsfrom the computational analysis which is carried out on aWindows 10 machine using an Intel i7-6700HQ processorwith 8GB of RAM CPLEX 126 optimization studio is usedto solve the mathematical models The analysis is organizedin two subsections single-objective and multiobjective opti-mizations

The results are interpreted in terms of satisfaction levelsof each objective A satisfaction level of 100 indicates thatthe objective is equal to its optimal level Conversely smallersatisfaction levels indicate that there is a gap between theobjective and its best achievable target Formally these levels

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

Journal of Advanced Transportation 7

Table 1 Safety distance from waste facilities

Criteria Sorting facility (km) Incinerator (km) Landfill (km)Residential area 1 2 1Archaeological heritage site 1 1 1River 1 1 1Pond - 03 03Main road - 03 03

Pathum ani

Bangkok

Phra Nakhon Si Ayutthaya

Nakhon Nayok

Saraburi

Nonthaburi

Figure 3 Central Thailand

subdistricts Wastes at collection centers are transported tosorting facilities and subsequently sent to either incineratorsor landfills Recycling is purposely not included in this studyas it is currently done by private companies The validation ofthe proposed model is done by determining the location andsize of sorting and disposal facilities

41 Parameters

Land Availability Assessment and Candidate Locations Inorder to quantify the land available an initial screening isnecessary to exclude from the analysis places such as riverspondsmain roads archaeological heritage sites and residen-tial areas We further include a buffering area to guaranteesafe distances between waste sites As shown in Table 1 thesize of these buffers is set according to the regulation andguideline of MSWM developed by the Pollution ControlDepartment (PCD)

A number of polygons are identified by combiningavailable land with subdistrict boundaries Based on theirsizes these polygons are further divided and their centroidis selected as a facility location Available land for landfillsiting is shown in Figure 4 Since candidate locations ofthe three types of facilities overlap we further constrain themathematical model to avoid colocations

To ensure environmental justice across the three districtswe perform the land-use assessment at the subdistrict levelFor any location within a subdistrict we compute parameters119904119878119895119897 119904119868119896119897 and 119904

1198711198961015840119897 as the following ratio

Direct + Indirect land use with facility of size 119897Total land available in the sub-district

(27)

For each facility 3 capacity levels are considered smallmedium and large Their direct and indirect land-use areshown inTable 2The values are estimated by land occupationLCIA methodology as previously described in our land-useimpact assessment

Traveling Distances All wastes are transported from the col-lection centers to the sorting facilities using 16-tonne (light)trucks From the sorting facilities to both the incineratorand landfill sites 32-tonne (heavy) trucks are used Travelingdistances are estimated using ArcGIS and a digital map ofPathum Thani Specifically having defined the candidatelocations we use a network analysis tool to determine theshortest routes

Public Health Impact Assessment To measure the publichealth impact this study computes the DALYs for peopleaffected by the MSWM system The first step is to estimatethe number of people living near the supply chain No datais currently available showing the population distribution atthe household level ArcGIS is used to count the total numberof residential buildings surrounding the waste transportationroutes and MSWM facilities

To estimate the damage to public health caused by anMSWM system this study adopts the emission-to-exposuremodel used byGouge et al [37] andGreco et al [38]They useseveral buffer distances to estimate the health impact causedby transport pollution In our study we set the buffer distancefor transportation routes to 100m For MSWM facilities theaffected areas are assumed to increase with the waste disposaldimension Moreover due to a long history of unsanitarypractices in Thailand landfills are assumed to have a largerimpact than other MSWM facilities (Table 3)

The estimation of the number of affected people is madebased on the information of the total population living in thearea and the number of residential buildings The proposedestimation approach is expected to give a more accurateestimate of affected people than the previous approach [39]Varying impact distances corresponding to different typesand sizes of facilities are used instead of one single impactdistanceThe second step is tomultiply the number of affected

8 Journal of Advanced Transportation

Nonthaburi

Bangkok

Pathum ani

Candidate landfill siting locationsUnsuitable area for landfill siting

Figure 4 Landfill locations

Table 2 Direct and indirect land-use impacts

Direct land-use (1198982) Indirect land-use (1198982)Waste facility Small size Medium size Large size Small size Medium size Large sizeSorting facility 4800 8000 16000 6191 10780 21559Incinerator 8000 16000 24000 11971 23941 35911Landfill 80000 160000 192000 127770 255525 335295

Table 3 Facilities impact on public health

Facilities Sized Capacity (tonneday) Affected areas (km) DALYs

Sorting FacilitySmall 50 03 007

Medium 100 06 014Large 300 18 028

IncineratorSmall 50 05 595

Medium 100 1 119Large 150 15 1785

LandfillSmall 50 1 389

Medium 100 2 778Large 150 3 1166

people near the transportation routes and MSWM facilitiesby the DALYs coefficients which are summarized in Tables 3and 4 The number of DALYs is estimated based on a 30-yearoperational period using the ReCiPe 2008 Endpoint LCIAmethod [33] Only local-scale environmental impacts aretaken into account including human toxicity photochemicaloxidant formation PM formation and ionizing radiationThe damage due to climate change and ozone depletion isneglected Finally the capacity of waste sites and trucks isselected from those available in SimaPro 73 (LCA software)which covers a wide range of typical facilities and operationsThe entire dataset can be found in Kachapanya [40]

42 Results and Discussion This section presents the resultsfrom the computational analysis which is carried out on aWindows 10 machine using an Intel i7-6700HQ processorwith 8GB of RAM CPLEX 126 optimization studio is usedto solve the mathematical models The analysis is organizedin two subsections single-objective and multiobjective opti-mizations

The results are interpreted in terms of satisfaction levelsof each objective A satisfaction level of 100 indicates thatthe objective is equal to its optimal level Conversely smallersatisfaction levels indicate that there is a gap between theobjective and its best achievable target Formally these levels

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

8 Journal of Advanced Transportation

Nonthaburi

Bangkok

Pathum ani

Candidate landfill siting locationsUnsuitable area for landfill siting

Figure 4 Landfill locations

Table 2 Direct and indirect land-use impacts

Direct land-use (1198982) Indirect land-use (1198982)Waste facility Small size Medium size Large size Small size Medium size Large sizeSorting facility 4800 8000 16000 6191 10780 21559Incinerator 8000 16000 24000 11971 23941 35911Landfill 80000 160000 192000 127770 255525 335295

Table 3 Facilities impact on public health

Facilities Sized Capacity (tonneday) Affected areas (km) DALYs

Sorting FacilitySmall 50 03 007

Medium 100 06 014Large 300 18 028

IncineratorSmall 50 05 595

Medium 100 1 119Large 150 15 1785

LandfillSmall 50 1 389

Medium 100 2 778Large 150 3 1166

people near the transportation routes and MSWM facilitiesby the DALYs coefficients which are summarized in Tables 3and 4 The number of DALYs is estimated based on a 30-yearoperational period using the ReCiPe 2008 Endpoint LCIAmethod [33] Only local-scale environmental impacts aretaken into account including human toxicity photochemicaloxidant formation PM formation and ionizing radiationThe damage due to climate change and ozone depletion isneglected Finally the capacity of waste sites and trucks isselected from those available in SimaPro 73 (LCA software)which covers a wide range of typical facilities and operationsThe entire dataset can be found in Kachapanya [40]

42 Results and Discussion This section presents the resultsfrom the computational analysis which is carried out on aWindows 10 machine using an Intel i7-6700HQ processorwith 8GB of RAM CPLEX 126 optimization studio is usedto solve the mathematical models The analysis is organizedin two subsections single-objective and multiobjective opti-mizations

The results are interpreted in terms of satisfaction levelsof each objective A satisfaction level of 100 indicates thatthe objective is equal to its optimal level Conversely smallersatisfaction levels indicate that there is a gap between theobjective and its best achievable target Formally these levels

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

Journal of Advanced Transportation 9

Table 4 Transportation impact on public health

Fleet types Capacity (ton) Affected areas (km) DALYs Empty load (per km) DALYs full load (per tkm)Light truck 16 01 582 sdot 10minus7 562 sdot 10minus8

Heavy truck 32 01 116 sdot 10minus6 112 sdot 10minus7

Table 5 Results of single-objective optimization

Minimizing Cost Minimizing AvgLand-Use Stress

Minimizing PublicHealth Impact

Total Cost (USD)

Total transportationcost 11973205 23519346 9658807

Total land cost 7753691 1854007 21035012Total construction

cost 17114396 19456136 27692869

Total operation cost 14103023 19823517 16354068Total cost 50944315 64653006 74740757

Satisfaction Level 100 42 0

Land-Use Impact Avg Land-use Stress 0573 0028 0985Satisfaction Level 43 100 0

Public Health Impact(DALY)

Transportation 13042 47868 6214Waste Facilities 31639 10072 1010

Total Public HealthImpact 44681 57940 7224

Satisfaction Level 26 0 100Average Satisfaction Level 56 47 33Computational Time (Sec) 24 10 13

are obtained from the deviation values introduced in themethodology section (ie 1 minus 120590119888 1 minus 120590119906 and 1 minus 120590ℎ)

421 Single-Objective Optimization

Total Cost Optimization (SWMN(119865119888)) Figure 5(a) shows theoptimal layout of the MSWM system obtained by solvingSWMN(119865119888) Results show that when cost is the main driverthe number of facilities is low Out of 37 candidate locationsfor sorting facilities only 6 are selected Similarly only 1incinerator and 3 landfills are selected While these facilitiesprovide sufficient capacity for all subdistrict they also gener-ate routes longer than 30 km

The summary of costs and the average land-use stressassociated with the solution are shown in Table 5 under thecolumn named ldquoMinimizing Costrdquo The construction costis the largest cost As a consequence landfills are chosenover incinerators The cost-optimum of the MSWM layoutis about 50944315 US dollars composed of the transporta-tion (11973205 US dollars) land (7753691 US dollars)construction (17114396 US dollars) and operational costs(14103023USdollars)The average land-use stress and publichealth impact for this solution are estimated at 0573 and44681 DALYs respectively The public health impact is fromtransportation (13042 DALY) and waste facilities (31639DALYs) This suggests that although SWMN(119865119888) achievesminimum cost it comes at the expense of public health andland-use This is mostly due to disposal sites located close

to the urban areas where waste is generated resulting inexcessive land-use stress and high public health impact

Average Land-Use Stress Optimization (SWMN(119865119906)) Numberand location of facilities obtained by solving SWMN(119865119906) areshown in Figure 5(b) Again the number of open facilitiesis relatively small Four sorting facilities and four incin-erators are selected The locations are different comparedto the SWMN(119865119888) case Sorting facilities and incineratorsare located in rural areas reducing the excessive land-usestress returned by the cost minimization model No landfillis selected However displacing facilities away from urbanareas leads to high transportation cost and high public healthimpact

The results of average land-use stress are shown inTable 5 under the column named ldquoMinimizing Avg Land-Use Stressrdquo The results show that the total cost is 64653006US dollars consisting of transportation cost (24053902 USdollars) land cost (1896146 US dollars) construction cost(19898341 US dollars) and disposal cost (20274072 USdollars) The average land-use stress of the MSWM systemdrops to 0028 The public health impact is 57940 DALYs(47868 DALYs from transportation and 10072 DALYs fromwaste facilities)

Public Health Impact Optimization (SWMN(119865ℎ)) SolvingSWMN(119865ℎ) leads to a layout that is quite differentMost of thefacilities are sparsely located across the region (Figure 5(c))

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

10 Journal of Advanced Transportation

Optimal layout of MSWM system under cost objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under Avg land use stress objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under public health impact objective

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Figure 5 Optimal layouts of MSWM system under single-objective functions

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

Journal of Advanced Transportation 11

Table 6 Results of multiobjective optimization

Bi-objective Tri-objective

Minimizing Costand Avg Land Use

Stress

Minimizing Costand Public Health

Impact

Minimizing AvgLand Use Stressand Public Health

Minimizing CostAvg Land Use

Stress and PublicHealth

Total Cost (USD)

Totaltransportation cost 13123748 12309316 12128780 10313519

Total land cost 6692561 10973973 12124521 10511253Total construction

cost 22465381 21349224 23941083 22864008

Total operationcost 17448975 16729273 19823509 17268910

Total cost 59730664 61361787 68017894 60957690Satisfaction Level 63 56 28 58

Land Use ImpactAvg Land-use

Stress 0159 0857 0242 0466

Satisfaction Level 86 13 78 54

Public HealthImpact (DALY)

Transportation 24483 17704 8997 8384Waste Facilities 31117 5050 4018 1342

Total Public HealthImpact 55600 22754 13015 9726

Satisfaction Level 5 69 89 95Average Satisfaction Level 51 46 65 69Computational Time (Sec) 37 35 33 82

A total of 22 facilities are opened (12 sorting facilities 5landfills and 5 incinerators) Results in Table 5 show thatthe optimal public health drops to 7224 DALYs The averageland-use stress and total cost increase to 0985 and 74740757US dollars respectively As expected the land cost (21035012US dollars) and construction cost (27692869 US dollars) aremostly responsible for the cost increment Clearly reducingpublic health is mostly a consequence of reducing thetransportation routes This is also evident by looking at thetransportation cost (9658807 US dollars) which decreasesconsiderably This is achieved by locating a large number offacilities sparsely across the area Consequently the land-useratio is bound to worsen dramatically

To sum up the transportation cost reaches its minimumwhen SWMN(119865ℎ) is solved Its value is 20 smaller thanSWMN(119865119888)However the land cost fromSWMN(119865119906 ) is lowerthan SWMN(119865119888) by 76 and it is lower than SWMN(119865ℎ) by91 For the total construction cost SWMN(119865119888) is 12 lowerthan SWMN(119865119906) because landfills have lower constructioncost than incinerators and it is 38 lower than SWMN(119865ℎ)because the number of sorting facilities is smaller The reasonis that incinerators reduce the amount of land required andthe cost of land in urban areas is typically more expensiveThe lowest operational cost is from SWMN(119865119888) Moreoverfocusing on the land-use stress impact SWMN(119865119906) results inlower values compared to SWMN(119865119888) and SWMN(119865ℎ) (95and 97 respectively) Finally regarding the public healthimpact the SWMN(119865ℎ) result is lower than SWMN(119865119888) by

approximately 84 and lower than SWMN(119865119906) by approxi-mately 88

422 Multiobjective Optimization The results and the lay-outs of MSWM networks are shown in Tables 6 and 7 andFigure 6

Total Cost and Average Land-Use Stress Optimization(SWMN(119865119888 119865119906)) When the problem is solved minimizingcosts and land-use sorting facilities and incineratorsare evenly distributed between urban and rural areasThe landfills are located in rural areas due to larger landrequirements (Figure 6(a)) This scenario shows the tradeoffbetween costs and land-use stress Looking at SWMN(119865119888)land-use stress satisfaction increases from 43 to 86 but itdeteriorates the total cost satisfaction level by 37 (Table 6)Due to the higher potential impact of landfill facilities on theoverall land-use stress SWMN(119865119888 119865119906) reduces the numberof facilities to only one large facility (Table 7) However tosatisfy the total demand three large incinerators are builtFurthermore the number of sorting facilities increases to 11(7 small 1 medium and 3 large) As expected this scenariohas high satisfaction levels of cost (63) and land-use stress(86) Nevertheless the satisfaction level of the public healthobjective is extremely low (5)

Total Cost and the Public Health Impact (SWMN(119865119888 119865ℎ))The results of optimizing costs and public health show that

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

12 Journal of Advanced Transportation

Optimal layout of MSWM system under cost and avg land

use stress objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(a)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(b)

Optimal layout of MSWM system under avg land use stress

and public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(c)

Optimal layout of MSWM system under cost avg land use stressand public health impact objectives

Collection center

Sorting Facility (small

Landfill (small

Incinerator (small medium

medium

medium

Large

Large

Large

)

)

)

Transportation routes from collectioncenter to sorting facilityTransportation routes from sortingfacility to disposal sites

(d)

Figure 6 Optimal layouts of MSWM system under multiobjective functions

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

Journal of Advanced Transportation 13

Table 7 Number of facilities in the optimization scenarios

ScenarioSorting Facility Incinerator Landfill Avg satisfaction

levelSmall size Medium size Large size Small size Medium size Large size Small size Medium size Large size

Minimizingcost

1 3 2 0 0 1 1 0 2 56

Minimizingavg landuse stress

2 0 2 1 0 3 0 0 0 47

Minimizingpublichealthimpact

5 6 1 3 2 0 5 0 0 33

Minimizingcost andavg landuse stress

7 1 3 0 0 3 0 0 1 51

Minimizingcost andpublichealthimpact

3 3 3 0 0 2 2 0 1 46

Minimizingavg landuse stressand publichealth

4 2 5 1 2 2 0 0 0 65

Minimizingcost avgland usestress andpublichealth

6 6 0 4 0 1 3 0 0 69

all facilities are sparsely distributed in urban and rural areas(Figure 6(b)) This is because the two objectives share thecommon goal of reducing the transportation routes so thatboth health and costs are reduced From Table 7 the sortingfacilities are now three for each size Two large incineratorsare built and three landfills locations are selected (2 small 1large) The average satisfaction is 46 The satisfaction levelof cost is 56 while the satisfaction level of public health is69 (Table 6) This result suggests a clear conflict betweenthese two objectives despite the common goal of reducingtransportation routes

Average Land-Use Stress and Public Health Impact(SWMN(119865119906 119865ℎ)) Optimizing land-use and health impactdisregarding costs results in selecting only incinerators (1small 2 medium and 2 large) due to their lower land-useas opposed to landfills (Figure 6(c)) The number of sortingfacilities increases to 11 5 of which are large 2 medium and4 small The average satisfaction level is 65 as land-usestress (78) and public health impact (89) simultaneouslyreach high levels (Table 6) However the satisfaction level ofthe total cost is reduced dramatically to 28 suggesting thatthis solution is not practical

Total Cost Average Land-Use Stress and Public Health Impact(SWMN(119865119888 119865119906 119865ℎ)) Previous results have shown that bothsingle- and biobjective models fail to reach a good compro-mise Therefore the problem is solved minimizing the threeobjectives at the same time This leads to an MSWM systemlayout that is well balanced across the region (Figure 6(d)) asthis model mainly chooses small and medium-sized facilities(Table 7) Normally it is difficult to obtain solutions with highsatisfaction levels across all conflicting objectives Howeverthis scenario gives the highest average satisfaction level(69) and offers an effective compromise between the threeobjectives as each satisfaction level is above 50

5 Concluding Remarks

In this paper we propose a novel network design optimiza-tion model for MSWM which accounts for sustainabilityin a comprehensive way Specifically we incorporate envi-ronmental and social impact indicators with the economicobjective A formal methodology is introduced to modelpublic health and land-use impacts The first is measuredin terms of DALYs imposed by the waste operations on

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

14 Journal of Advanced Transportation

the population living close to the supply chain To enforcea fair use across a cityrsquos subdistricts the land-use metricis computed as the ratio between used and available landThe multiobjective formulation is translated into a single-objective model aiming to minimize the maximum gap ofeach objective from its optimal target

A case study in Pathum Thani (Thailand) is developedto validate the model while also providing results that canbe of public interest to increase awareness and engage withlocal stakeholders The single-objective analysis highlightsthe fact that focusing only on cost generates a supply chainwhich imposes a serious burden on society In fact theresulting land-use and public health metrics are far fromsustainable However single-objective models focusing onpublic health or land-use are inefficient and they deterioratethe metrics outside the objective This further motivatesthe multiobjective approach studied in this paper wherea model is proposed to minimize the deviation of eachcriterion from its optimal target The best tradeoff betweenthe metrics is indeed achieved when all dimensions areconsidered simultaneously

The scope of this work together with an increasing pushfor a wide-range research focus on sustainability providesseveral interesting further extensions Integrated modelingapproaches should be developed to simultaneously considerinterrelated supply chain decisions as demonstrated byMotaand et al [41] To this aim optimization models can be devel-oped to incorporate facility location decisions with otherdecisions such as waste collection schemes transport modesand disposal technologies This will require developing andsolving complex multiobjective location-routing problemsAnother line of research should focus on incorporatinguncertainty into the problem It is clearly of interest toinvestigate the extent to which the problemrsquos features suchas the amount of waste the transportation costs and theirinherent uncertainties can impact sustainability metrics andcosts Finally given the complexity of the current model andits possible extensions a further research direction shouldfocus on the development of efficient solution algorithms toobtain good solutions on large realistic networks

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] L Bastin and D M Longden ldquoComparing transport emissionsand impacts for energy recovery from domestic waste (EfW)Centralised and distributed disposal options for two UK coun-tiesrdquo Computers Environment and Urban Systems vol 33 no 6pp 492ndash503 2009

[2] F Ncube E J Ncube and K Voyi ldquoA systematic criticalreview of epidemiological studies on public health concerns ofmunicipal solid waste handlingrdquo Perspectives in Public Healthvol 137 no 2 pp 102ndash108 2016

[3] L A Nwaogu C O Ujowundu C I Iheme T N Ezejiofor andDC Belonwu ldquoEffect of sublethal concentration of heavymetalcontamination on soil physicochemical properties catalase anddehydrogenase activitiesrdquo International Journal of BiochemistryResearch amp Review vol 4 no 2 pp 141ndash149 2014

[4] G Owusu E Nketiah-Amponsah S N A Codjoe and RL Afutu-Kotey ldquoHow do Ghanas landfills affect residentialproperty values A case study of two sites in Accrardquo UrbanGeography vol 35 no 8 pp 1140ndash1155 2014

[5] V Spoann T Fujiwara B Seng and C Lay ldquoMunicipal solidwaste management Constraints and opportunities to improvecapacity of local government authorities of Phnom Penh Capi-talrdquoWasteManagementamp Research vol 36 no 10 pp 985ndash9922018

[6] G Owusu ldquoSocial effects of poor sanitation and waste man-agement on poor urban communities a neighborhood-specificstudy of Sabon Zongo Accrardquo Journal of Urbanism vol 3 no 2pp 145ndash160 2010

[7] V Ibanez-Fores M D Bovea C Coutinho-Nobrega and H Rde Medeiros ldquoAssessing the social performance of municipalsolid waste management systems in developing countriesProposal of indicators and a case studyrdquo Ecological Indicatorsvol 98 pp 164ndash178 2019

[8] P Ferrao P Ribeiro J Rodrigues et al ldquoEnvironmentaleconomic and social costs and benefits of a packaging wastemanagement system a portuguese case studyrdquo Resources Con-servation amp Recycling vol 85 pp 67ndash78 2014

[9] H Yuan ldquoA model for evaluating the social performance ofconstruction waste managementrdquo Waste Management vol 32no 6 pp 1218ndash1228 2012

[10] H Ak and W Braida ldquoSustainable municipal solid wastemanagement decision making Development and implemen-tation of a single score sustainability indexrdquo Management ofEnvironmental Quality An International Journal vol 26 no 6pp 909ndash928 2015

[11] J LMoura A Ibeas andL dellrsquoOlio ldquoOptimization-simulationmodel for planning supply transport to large infrastructurepublic works located in congested urban areasrdquo Networks andSpatial Economics vol 10 no 4 pp 487ndash507 2010

[12] E M Ferguson J Duthie A Unnikrishnan and S T WallerldquoIncorporating equity into the transit frequency-setting prob-lemrdquo Transportation Research Part A Policy and Practice vol46 no 1 pp 190ndash199 2012

[13] H R Jafari M Seifbarghy and M Omidvari ldquoSustainablesupply chain design with water environmental impacts andjustice-oriented employment considerations a case study intextile industryrdquo Scientia Iranica vol 24 no 4 pp 2119ndash21372017

[14] KManaughM G Badami and AM El-Geneidy ldquoIntegratingsocial equity into urban transportation planning a criticalevaluation of equity objectives and measures in transportationplans in north americardquo Transport Policy vol 37 pp 167ndash1762015

[15] M O Beiler and M Mohammed ldquoExploring transportationequity Development and application of a transportation justiceframeworkrdquo Transportation Research Part D Transport andEnvironment vol 47 pp 285ndash298 2016

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

Journal of Advanced Transportation 15

[16] A Bernstad Saraiva R G Souza C FMahler andRA B ValleldquoConsequential lifecycle modelling of solid waste managementsystems ndashReviewing choices and exploring their consequencesrdquoJournal of Cleaner Production vol 202 pp 488ndash496 2018

[17] A P Rodrigues M L Fernandes M F F Rodrigues S CBortoluzzi S E Gouvea da Costa and E Pinheiro de LimaldquoDeveloping criteria for performance assessment in municipalsolid waste managementrdquo Journal of Cleaner Production vol186 pp 748ndash757 2018

[18] Y M Zhang G H Huang and L He ldquoAn inexact reverselogisticsmodel formunicipal solidwastemanagement systemsrdquoJournal of Environmental Management vol 92 no 3 pp 522ndash530 2011

[19] E A Toso and D Alem ldquoEffective location models for sortingrecyclables in public managementrdquo European Journal of Opera-tional Research vol 234 no 3 pp 839ndash860 2014

[20] D Inghels W Dullaert and D Vigo ldquoA service networkdesign model for multimodal municipal solid waste transportrdquoEuropean Journal ofOperational Research vol 254 no 1 pp 68ndash79 2016

[21] Z Xu A Elomri S Pokharel Q Zhang X GMing andW LiuldquoGlobal reverse supply chain design for solid waste recyclingunder uncertainties and carbon emission constraintrdquo WasteManagement vol 64 pp 358ndash370 2017

[22] M Eskandarpour P Dejax J Miemczyk and O PetonldquoSustainable supply chain network design An optimization-oriented reviewrdquo OMEGA - The International Journal of Man-agement Science vol 54 pp 11ndash32 2015

[23] H Khandelwal H Dhar A K Thalla and S Kumar ldquoApplica-tion of life cycle assessment in municipal solid waste manage-ment a worldwide critical reviewrdquo Journal of Cleaner Produc-tion vol 209 pp 630ndash654 2019

[24] P Yadav and S R Samadder ldquoA critical review of the lifecycle assessment studies on solid waste management in Asiancountriesrdquo Journal of Cleaner Production vol 185 pp 492ndash5152018

[25] N S Kubanza D K Das and D Simatele ldquoSome happyothers sad exploring environmental justice in solid wastemanagement in kinshasa the democratic republic of congordquoLocal Environment vol 22 no 5 pp 595ndash620 2017

[26] N S Kubanza and D Simatele ldquoSocial and environmentalinjustices in solid waste management in sub-saharan africaa study of kinshasa the democratic republic of congordquo LocalEnvironment vol 21 no 7 pp 866ndash882 2016

[27] N S Kubanza and D Simatele ldquoSustainable solid waste man-agement in sub-Saharan African cities application of systemthinking and system dynamic as methodological imperatives inkinshasa the democratic republic of congordquo Local Environmentvol 23 no 2 pp 220ndash238 2018

[28] K Kelobonye G McCarney J C Xia M S H Swapan F Maoand H Zhou ldquoRelative accessibility analysis for key land uses aspatial equity perspectiverdquo Journal of Transport Geography vol75 pp 82ndash93 2019

[29] J Njeru ldquoThe urban political ecology of plastic bag wasteproblem in Nairobi Kenyardquo Geoforum vol 37 no 6 pp 1046ndash1058 2006

[30] J Agyeman and T Evans ldquoToward just sustainability in urbancommunities building equity rights with sustainable solutionsrdquoAnnals of the American Academy of Political and Social Sciencevol 590 no 1 pp 35ndash53 2003

[31] J M Norton S Wing H J Lipscomb J S Kaufman S WMarshall and A J Cravey ldquoRace wealth and solid waste

facilities in North Carolinardquo Environmental Health Perspectivesvol 115 no 9 pp 1344ndash1350 2007

[32] C J LMurray ldquoQuantifying the burdenof disease the technicalbasis for disability-adjusted life yearsrdquo Bulletin of the WorldHealth Organization vol 72 no 3 pp 429ndash445 1994

[33] M Goedkoop R Heijungs M Huijbregts A De Schryver J VZ R Struijs and R V Zelm ldquoReCiPe 2008 A life cycle impactassessment method which comprises harmonised categoryindicators at the midpoint and the endpoint levelrdquo First editionReport I Characterisation 2009 httpwwwlcia-recipenet

[34] L M I Canals C Bauer J Depestele et al ldquoKey elements ina framework for land use impact assessment within LCArdquo TheInternational Journal of Life Cycle Assessment vol 12 no 1 pp5ndash15 2007

[35] T Koellner L De Baan T Beck et al ldquoUNEP-SETAC guidelineon global land use impact assessment on biodiversity andecosystem services in LCArdquo The International Journal of LifeCycle Assessment vol 18 no 6 pp 1188ndash1202 2013

[36] PCD ldquoSolid waste of community management in 2016rdquo Pol-lution Control Department Report Pollution Control Depart-mentThailand 2016

[37] B Gouge H Dowlatabadi and F J Ries ldquoMinimizing thehealth and climate impacts of emissions fromheavy-duty publictransportation bus fleets through operational optimizationrdquoEnvironmental Science amp Technology vol 47 no 8 pp 3734ndash3742 2013

[38] S L Greco A M Wilson J D Spengler and J I LevyldquoSpatial patterns of mobile source particulatematter emissions-to-exposure relationships across theUnited StatesrdquoAtmosphericEnvironment vol 41 no 5 pp 1011ndash1025 2007

[39] S Olapiriyakul ldquoDesigning a sustainable municipal solid wastemanagement system in PathumThani Thailandrdquo InternationalJournal of Environmental Technology and Management vol 20no 1-2 pp 37ndash59 2017

[40] W Kachapanya Sustainable solid waste management systemin urban areas of Pathum Thani Thailand (Master of ScienceManagement Mathematics) Sirindhorn International Instituteof Technology ThammasatUniversity 2018 httpsdrivegooglecomdrivefolders14Okc0vUmjCHbgkBCdqLbPR1Gy7lDVaVg

[41] B Mota M I Gomes A Carvalho and A P Barbosa-PovoaldquoSustainable supply chains An integrated modeling approachunder uncertaintyrdquo OMEGA - The International Journal ofManagement Science vol 77 pp 32ndash57 2018

International Journal of

AerospaceEngineeringHindawiwwwhindawicom Volume 2018

RoboticsJournal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Active and Passive Electronic Components

VLSI Design

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Shock and Vibration

Hindawiwwwhindawicom Volume 2018

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawiwwwhindawicom

Volume 2018

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

Control Scienceand Engineering

Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom

Journal ofEngineeringVolume 2018

SensorsJournal of

Hindawiwwwhindawicom Volume 2018

International Journal of

RotatingMachinery

Hindawiwwwhindawicom Volume 2018

Modelling ampSimulationin EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Navigation and Observation

International Journal of

Hindawi

wwwhindawicom Volume 2018

Advances in

Multimedia

Submit your manuscripts atwwwhindawicom