transportationinfrastructureprojectfinancing;highways

Research ArticleTransportation Infrastructure Project Financing HighwaysCapital Structure Design Techniques

Hanieh Soleymani 1 Mehdi Ravanshadnia 1 and Mehdi Montazer2

1Department of Construction Engineering and Management Faculty of Civil Engineering Science and Research BranchIslamic Azad University Tehran Iran2Department of Law Damavand Branch Islamic Azad University Damavand Iran

Correspondence should be addressed to Mehdi Ravanshadnia ravanshadniasrbiauacir

Received 31 July 2021 Revised 19 August 2021 Accepted 25 August 2021 Published 18 October 2021

Academic Editor S Mahdi S Kolbadi

Copyright copy 2021 Hanieh Soleymani et al (is is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

Whether a private bidder can win a concession depends largely on advanced financial engineering techniques numerous methodswere developed Meeting large infrastructure needs including its proper maintenance and operation is and will remain a majorchallenge for the all-around the in the coming years requiring targeted innovative financing mechanisms Even though it isrecognized that there are three types of financial instruments equity mezzanine finance and debt in funding an infrastructureproject the status quo is that previous capital optimization methods did not consider mezzanine finance or simply categorized itinto debt-like or equity-like instruments (e global infrastructure sector is witnessing a steady growth of private equity in-vestment in mezzanine instruments (e frequent usage of the contingent claim embedded in mezzanine financing makes thetraditional model for capital structure optimization invalid (is study presents a more advanced method to optimize capitalstructure in infrastructure financing (is easily implemented method is based on a two-stage procedure I) identification ofoptimal stopping time for convertible securities and II) capital structure optimization by a conventional model (e quantitativeoptimization model can be easily generalized (e global infrastructure sector is witnessing the continued growth of a privateequity fund of mezzanine tools Repeated use of potential claims embedded in mezzanine financing has invalidated the traditionalmodel for optimizing capital structure

1 Introduction

Governments have traditionally used their budget resourcesfor many years to do activities and projects But increasingneed to build and manage infrastructure projects have al-ways been a big challenge along with a lack of funding torealize them [1] (is large limitation on one of the mostimportant resources needed to do projects has led ownersand even contractors to supply these resources in differentways [2] Public owners of infrastructure projects thatoriginally bore the brunt of infrastructure financing with avariety of infrastructure financing structures have to face adaunting challenge of balancing the need for high costs andlimited budgets [3] So states around the world are looking

for new alternatives economically efficient [4] (is projectoffers a few quantities strategies that can facilitate thepresence of private investors in infrastructure financingOne of the basic preconditions for the success of any projectis access to sufficient and timely resources proper man-agement of financial resources and their optimal use [5](is is so important that without sufficient financial andtimely resources the project will not be implemented or notachieve its predetermined goals [6] Development of ade-quate and efficient transport infrastructure is one of theimmediate priorities of all SADC member States just as isthe case for any country especially the developing countries[7] Such infrastructure is key to facilitating the realisation ofthe aspirations for rapid economic and social development

HindawiShock and VibrationVolume 2021 Article ID 4988577 8 pageshttpsdoiorg10115520214988577

necessary for uplifting the standards of living of the citizensand hence eradication of poverty [8]

Optimization of the Public-Private Partnership (PPP)strategies for private bidders to ensure the economic jus-tification of the investment [9] Optimization of the capitalstructure has been a concern for financial designers duringdecades Although the topics of financial theory have fullyexplored how to optimize the capital structure in corporatefinance [10] (us the challenge of infrastructure capitalstructuring is based on a combination of financial instru-ments pillars including stock debt and mezzanine capital[11] In freeway projects toll revenues are the main source ofrepayment of project loans and debts distribution of projectshares and the financing for all operations and maintenanceof freeway facilities [12] (us an accurate and reliableestimation of traffic demand and a reduction of an effectivedemand risk are two vital activities that must be consideredto achieve successful implementation of public-privatefreeway participation projects [13] (ere are many quan-titative methods to assess demand risk on toll roadshowever none of proposed methods have considered acomprehensive method for calculating user behaviours suchas population-based behaviours and socio-economic be-haviours travel expenses freeway communication andnetwork efficiency and the level of free service None ofthese methods have considered the effect of agents on eachother and cause and effect relationships between differentagents Demand forecasting and traffic analysis in tollfreeway projects should be examined more thoroughly toconsider the actual path-choosing behaviours interactionsbetween different agents and their cause and effect rela-tionships [14] (e basic options or sources available forfinancing infrastructure development include public fi-nancing development assistance or grants from donorsprivate sector financing (by private project developers)borrowing from financing institutions (multilateral inter-national regional and local) and from internally generatedfunds by operating institutions [15]

11 Literature review To design the financing to determinethe amount of project financing as a partner brought and therest of the resources required for the project as borrowing(the range of tools is shown in Figure 1) [16] Projectborrowing refers to funds lent to the executing firm by fi-nanciers such as commercial banks insurance companiesand retirement funds as well as international institutions[17] (ese loans are secured by project-related assets [18]Lenders receive the principal and interest of their loansunder any circumstances whether the company makes aprofit or a loss [19] However to ensure that there is asufficient and strong financial capacity to repay projectborrowings lenders carefully monitor projected cash flowOften a special form of financing called quasi-capital is usedto attract risk-averse investors For this purpose a specialtype of company stock is issued called preferred stockPaying preferred stockholders takes precedence over ordi-nary stockholders but is higher than those sought by projectfinanciers and other creditors of the company [20]

(is group which itself has different forms is calledMezzanine Finance A project may use other tools such asleasing addition to borrowing methods partnersrsquo contri-bution and combined financing Leasing is more practical insome countries [21] Loan terms vary from bank to bank andborrower to borrower [22] Loans may have floatingfixedinterest rates [23] Partnersrsquo contributionmay be financed byproject investors investment funds international institu-tions domestic and foreign institutional investors (such asretirement funds) or the issuance of company shares indomesticforeign stock markets (Figure 2)

(e investment pyramid is a visual description of theprinciples by which investors should arrange their invest-ment portfolio so that each amount of money invested has adifferent level of risk [24] In this regard the largest amountof money invested should have the least risk and a small partof the money should be invested in high risk assets (isprinciple ensures that peoplersquos investments do not fluctuatesharply during shocks and market downturns (e foun-dation of a pyramid investment includes secure and highlyliquid investments such as savings accounts or short-termdeposit certificates [25] Security and easy access to thisinvestment can be considered as high returns higher riskinvestments and lower liquidity However having such abase amount of available and available investments meansthat investors can quickly turn their investments into moneywhen faced with unexpected costs (is prevents the sale oflong-term investments or investments with low liquidity andcreates costs for the investor (Figure 3)

(e issue of how companies select and adjust theirfinancial resources has been the focus of many financialeconomists for a long time and is still the subject of muchdebate [26] Of course once it was believed that the natureof such issues is so complex that it is not possible toformulate a reasonable theory at this time About half acentury ago opened the debate over the possibility offormulating such theories and eventually the continuationof such debates led (Figure 4) Studies show that since thepublication of their article various theories and modelshave been expressed as the capital structure of companiesand how to choose it [26] For information about relatedtheories and patterns see Harris and Raviorsquos valuableextensive work However research shows the agentsinfluencing the capital structure of companies and providea definitive answer to the following question Why does anumber of companies choose the option of issuing sharessome of them use of internal resources and others themethod of borrowing for their financing activities in dif-ferent circumstances [27 28]

Concessionary financeGuarantees Expert credits

Commercial lendingFinance

Figure 1 Range of financial instruments

2 Shock and Vibration

(e next step in a pyramid scheme is investing in thingslike long-term certificates of deposit government securitiesand buying bonds from companies that are financially andadministratively sound these investments have a reasonablereturn because they pay a fixed interest rate on the moneyinvested (e risk of losing money on these investments isalso very low but certificates of deposit and bonds havematurities meaning that the money invested by individualsplus interest is repaid to them Because these investmentsmay incur losses if they arrive earlier than the due dateinvestors should plan not to cash them out before the duedate Shares and mutual funds can have good returns andallow investors to make significant profits by selling them atlow prices as well But a slump in the stock market reducesthe value of stocks and the losses of investors (e potentialreturn on stocks and mutual funds as well as their risk putsthem at the top of the investment pyramid Most peoplersquosmoney goes to equity stocks and mutual funds which areconsidered safe investments in terms of rankings and asmall amount of peoplersquos money goes to very high-riskinvestments

2 Materials and methods

21 Agent-based Modeling (ABM) Discrete event simula-tions and dynamic systems have long been taught in uni-versities Students in the fields of industry managementeconomics operations research [28] are among the groupsthat simulation is taught in universities But in the realworld there is no interaction between the groups of discreteevent simulations and the groups of dynamic systems andthese two groups carry out scientific activities as twocompletely independent groups [2] In recent years factor-based modeling and simulation has become a purely aca-demic topic (is factor-based modeling approach is able tomodel and simulate intelligent structures and systems andtheir interactions with each other so in this report a pre-liminary explanation of this type of simulation is providedFactor-based simulation is a model involving one or morefactors along with the environment in which the agents arelocated in a way that allows agents to interact communicateand make decisions [3] In fact an agent-centric model has adynamic bottom-up structure [4] (is means that the ac-tivity of its components which are agents produces acomprehensive and coherent result which is called the eventresult (ese models typically encounter complex systemsand issues and have innovative capabilities [5] (is makes itmore difficult to identify the basic concepts and hypothesesfor this approach than the System Dynamics (SD) approach[21] states three characteristics for agents that each agentmust have at least two of three characteristics as shown inFigure 5 [29]

(e agent is a system that fulfills a set of goals in acomplex and dynamic environment (e agent is in anenvironment and can sense the environment through itssensors and act on it through its operatorsldquoAgents can beused in the role of individuals a group of individuals livingbeings and in some cases in the role of inanimate objectssuch as houses and cars (ere are many characteristics foragents but what is most agreed upon and emphasized is the

Bank Debt

Corporate bonds

Convertable securities

Preferredsecurities

Stocks Capital Growth

Growth and Income

Income

Preservation ofCapital

Balancing Risk amp Reward

e investment pyramididentified the hierarchy of

investorsStocks represents a higher degree

of risk

Increase

d Safet

y of P

rincip

al

Increased Risk

Figure 2 (e investment pyramid identified the hierarchy of investors

UtilityRestructuring

corporatizationdecentralization

Civil worksServices

contractsManagement amp

operating contracts LeasesaffermageConcessions

BOTDBO

Join ventures Privatizationfulldivestitures

Figure 3 Share of private sector capital based on participation

Projectsystem

Generalenvironment

Economic ampFinancial ForcesLegal amp Social

Forces

InternationalForces

PoliticalForces

TechnologicalForces

Specific Environment

Government

Lenders Sponsors ampInvestors

Creditors

SuppliersCostumers Competitors

Employees

Figure 4 Analyze the business environment and make a rea-sonable assessment

Shock and Vibration 3

category of autonomy and decision-making power byagents (e factor-based modeling approach starts from thesmallest independent and decision-making person and usesthe so-called bottom-up process(e set of behaviors of eachindividual in relation to the environment and other people(other factors) forms a generality that can be analyzed andexamined by the model (e agent-based modeling per-spective is based on automation and agent-based activity(at is a system behavior that results from the individualbehavior of the system is simulated in time steps (emodeler interprets the relationships between variables andthe conditions under which the system changes to a numberof simple rules that can move the system from one state toanother(e laws of change are actually principles that makeit possible for one variable to affect another Factor-basedsimulation is the best way to model where we are faced withintelligent factors such as humans In fact it can be said thatthis method is one of the best simulation methods in socialand scientific environments that face a limited number or alarge number of people [30]

211 Combined simulation (e interest in using a com-bined simulation approach given the nature and variety ofcombined simulation models there are few guidelines formodelers [31] Combined simulation models are needed indifficult situations to create more realistic models [32]While a system may only be modeled by a simulation ap-proach a combined simulation approach can be developedto increase the model effectiveness and transparency (egrowing interest in combined simulation methods can beattributed to advances in simulation training [17] Com-bined simulation work in the manufacturing industry fo-cuses on the potential benefits that the manufacturingindustry obtains them from a combined simulation [33]Combined systems can be modeled on different ways bycombining different basic model structures to achieve dif-ferent goals [34] (ese models present complementaryapproaches to simulation [35] Combined modeling in themanufacturing industry seeks to consider complex behaviorof manufacturing systems [36] However to consider

complex behavior of manufacturing systems the combinedmodeling framework must be able to consider all types ofinteractions within the combined model and assist themodel manufacturer well-defined and understandablecombined model designs to create (SM [37]

3 Analysis and discussion

31 Stochastic capital structure in infrastructure financingProject or infrastructure financing is a financing method oflarge-scale projects with large capital volumes long-termfinancial constraints with limited or no recourse imple-mented through a franchise business (SMS [38] (e generalstructure of the agent-based simulation framework shownbelow with the proposed model of agent-based trafficsimulation can be done at a more complete level according tothe simulation scheduling steps and traffic activities (Fig-ure 6) Traditionally ordinary capital is provided throughloans or shares in private infrastructure financing Debtfinancing can include bank debt financing through bondissuers or both [39] While bank debt is a common tool forinfrastructure financing bonds are another popular tool forfixed income debt in an infrastructure project financingAlthough most of the stock is financed by foreign share-holders such as commercial banks and credit companies butproject developers need to provide more capital stock toshow their ability and commitment to the project (Figure 7)Investorsrsquo stock returns often take the form of dividends orshareholders can cash their dividends by selling their or-dinary shares to other shareholders before the end of theconcession

32 Optimization of capital structure in infrastructurefinancing In 2020 Zhang proposed a similar but morequantitative model to optimize the capital structure ofpublic-private infrastructure projects considering the futurecash flow uncertainty of the operating period (e centralmethodology of these two studies according to a win-winprinciple is to provide a maximum of investorsrsquo stockreturns just like the principle and interest of lenders Inother words from the point of view of stock investors theoptimal capital structure is considered to be a combinationof stocks and debts which maximizes the Net Present Value(NPV) of the project by removing barriers of the project riskand analysing the justification and financial sustainability ofthe project From the point of view of financial models theoptimization problem of a certain capital structure creates akind of cycle in calculations the amount of Earnings beforeInterest and Taxes (EBIT) before determining a quantity offinancial instruments is not clear(is problem can be solvedby trial and error as shown in the Figure 8

33 Optimization of the stochastic capital structureIncreasing profits in PPPs have revolutionized the use ofmezzanine financial instruments to finance infrastructurearound the world for private stock investors (usaccording to its various aspects capital resources can bedivided into quasi-equity capital (such as preferred stock)

Time dependenttrip table

path vehicle simulation

Assignmentrules

Time dependentflow pattern

Figure 5 (e simulation process revolves around a set of au-tonomous factors


LE quasi-debt capital (such as project securities) LD andconvertible capital (such as convertible securities) LM re-spectively In the following a more advanced method isproposed to optimize the stochastic capital structure byentering Stockpile Disposal ProgramSemi-definite Program(SDP) to identify the stochastic optimal capital structure

Despite identification of the dynamic stopping time theoptimization process of a certain capital structure changes totwo optimization stages of the stochastic capital structure inFigure 9

34 Identifying the optimal stopping time with SDPDuring the year τk the holder of convertible securitiesdecides on the application of long-term debt transfer toshares (e holder can appear as a shareholder when theoutstanding debt is less than the expected conditional valueof future earnings Suppose that the conversion rate Kj inyear j is clearly specified at the beginning of the contract andthe shareholder can only receive his interest through divi-dends If the holder of convertible securities decides to applythe right in the year τk the amount of the share that the

Basic level

Description of theagent


Networkpresentation

Agent-driven traffic simulation

Highway environment Agent simulation

Physical components of the highway

Highway operational component

Multiple class travel agent

Agent decision making

Total traffic simulation output

Total flow pattern Measure highway performance

Figure 6 (e general structure of the factor-based simulation framework shown by the proposed traffic simulation model

Business processlife cycle

management

design

modeling

execution

monitoring

optimization

Figure 7 (e general trend of stochastic capital structure in in-frastructure financing

Asset based loans

Senior secured dept

Senior unsecured dept

Subordinated dept

Preferred equity

Common equity

Figure 8 (e general trend of optimization of capital structure ininfrastructure financing


stakeholder can have in the simulation path k is equal to Qτk

and calculated by the equation 2 So the NPV of dividendshe can collect is calculated by equation 7 In a year τk theholder of convertible bonds only needs to compare hisoutstanding loan with the expected conditional value of theequation 8

Qτk 1113944

T

jτk

PMj

Kτk

(1)

Sτk 1113944

T

jτk

NAC(jk) middot eminus remiddot jminus τk( )

Qτk

1113936 LE middot CiP1113872 1113873 + Qτk

(2)

Max 1113944T

τk

PMj1113872 1113873

⎧⎪⎨

⎪⎩

⎫⎪⎬

⎪⎭ E Sτk

|Fτk1113960 1113961

⎡⎢⎢⎢⎢⎢⎣⎤⎥⎥⎥⎥⎥⎦ (3)

Where Fτkis available information of the holder of con-

vertible bonds in the year τk (us when the expectedconditional value of convertible bonds is not more than theoutstanding debt the holder will choose to apply his con-version right One of the drawbacks of combining MultipleComplex System (MCS) with SDP is that NPV dividends arenot exactly measurable (is is because SDP estimates thecontinuing value determines a non-optimal action strategyand therefore naturally offers a lower price range Onemethod for estimating the continuing value is using a re-gression-based approach such as the Least Squares Method(LSM) method (e basic idea behind the LSM is thatconditional expectation E[Sτk

|Fτk] can be approximated in

each year of application with least squares regression alongwith MCS cross-sectional data Indeed in the year τkE[Sτk

|Fτk] can be represented as a linear combination of

basic orthonormal functions pi(EBIT(jmiddotk) such as thePower Laguerre Hermite and Legendre polynomials

E Sτk|Fτk

1113960 1113961 1113944infin

i0aipi EBIT τkk( )1113874 1113875 (4)

1113954a i1Z 1113944Z

i0aipi EBIT τkk( )1113874 1113875 minus Sτk

2

(5)

NPVOptL

OptE L

OptD L

OptM1113872 1113873 max NPV LE LD LM( 11138571113864 1113865forall

middot LE LD LM( 1113857

(6)

4 Conclusion

(e most important risk in projects implemented with aPPP system and for which non-recourse or limited re-course financing (project or structured) is considered isthe risk of revenue based on traffic demand A demandforecast can be considered as the most important part ofthe planning stage of road PPP projects Traffic demand isa direct determinant directly related to revenue levels andtoll rates Optimistic traffic forecast in many projects hasled to many problems in the financial structure of projectsSometimes optimistic forecast along with a traffic levelhas had irreversible effects in early years of the projectDemand forecast will include several evaluation methodswhich will used various economic and social parametersnetwork road conditions and various design patternchanges to predict the traffic level of the transportationsystem Demand forecast is a difficult activity that requiresa lot of studies For strategic project planning the feasi-bility of alternative strategies and demand for uniquecomponents of these strategies should be assessed atpredictions In corridor planning in the forecastingprocess the adequacy and quality of the service withcurrent facilities as well as potential needs for promotingthese facilities should be evaluated To plan facilities in theforecasting process the capacity of new facilities that maybe built or the capacity of existing road facilities should beevaluated (is study has offered a framework in order topresent available generic and specific benefits to eachproject stakeholder and it provides the required moti-vation for project owners to use and implement it in theirfuture projects As a result in short whether a privatecompany can earn a project credit depends heavily on thecapital cost of a private infrastructure project With ad-vanced financial engineering techniques several methodshave been developed to find the right combination ofstocks and debts Although three types of financial in-struments including stock mezzanine and debt are de-fined in the infrastructure financing project (e currentsituation is such that the usual optimization methods ofmezzanine financing are not considered or simply con-sidered as quasi-equity or quasi-debt Accordingly con-structability improvements have become the concern ofconstruction industry practitioners Considering con-structability issues in the early stages of the project en-hances identifying design limitations that preventcapabilities of contractors to take part in planning andimproving project performance (e purpose of this studyis identifying the prerequisites of constructability to re-solve the current problems of projects including inap-propriate plans without implement ability poor decisionmaking in design and lack of sufficient implementationexperience in the design engineering team

Fina

ncia

l var

iabl

es

Dependentvariables

Independentvariable

Control variable

Figure 9(e general trend of optimization of the stochastic capitalstructure


Data Availability

Requests for access to these data should be made to [thecorresponding author email address ravanshadniasrbiauacir]

Conflicts of Interest

(e author(s) declare(s) that there is no conflict of interestregarding the publication of this paper

Acknowledgments

An Acknowledgements section is optional and may rec-ognise those individuals who provided help during the re-search and preparation of the manuscript

References

[1] C Li L Hou B Sharma et al ldquoDeveloping a new intelligentsystem for the diagnosis of tuberculous pleural effusionrdquoComputer Methods and Programs in Biomedicine vol 153pp 211ndash225 2018

[2] M Wang C Huiling Y Bo et al ldquoToward an optimal kernelextreme learning machine using a chaotic moth-flame opti-mization strategy with applications in medical diagnosesrdquoNeurocomputing vol 267 pp 69ndash84 2017

[3] J Xia C Huiling Li Qiang et al ldquoUltrasound-based differ-entiation of malignant and benign thyroid Nodules an ex-treme learning machine approachrdquo Computer Methods andPrograms in Biomedicine vol 147 pp 37ndash49 2017

[4] H-L Chen W Gang Ma Chao C Zhen-Nao L Wen-Binand W Su-Jing ldquoAn efficient hybrid kernel extreme learningmachine approach for early diagnosis of Parkinson s diseaserdquoNeurocomputing vol 184 pp 131ndash144 2016

[5] L Shen L Xin-Yuan and H Min ldquoEvolving support vectormachines using fruit fly optimization for medical data clas-sificationrdquo Knowledge-Based Systems vol 96 pp 61ndash75 2016

[6] L Hu G Hong J Ma X Wang and H Chen ldquoAn efficientmachine learning approach for diagnosis of paraquat-poi-soned patientsrdquo Computers in Biology and Medicine vol 59pp 116ndash124 2015

[7] R Samimpey and E Saghatforoush ldquoA systematic review ofprerequisites for constructability implementation in infra-structure projectsrdquo Civil Engineering Journal vol 6 no 3pp 576ndash590 2020

[8] M Alinezhad S Ehsan K Zahra and P ChristopherldquoAnalysis of the benefits of implementation of IPD forconstruction project stakeholdersrdquo Civil Engineering Journalvol 6 pp 1609ndash1621 2020

[9] X Xu and H-L Chen ldquoAdaptive computational chemotaxisbased on field in bacterial foraging optimizationrdquo SoftComputing vol 18 no 4 pp 797ndash807 2014

[10] Y Zhang L Renjing A H Ali et al ldquoTowards augmentedkernel extreme learning models for bankruptcy predictionalgorithmic behavior and comprehensive analysisrdquo Neuro-computing 2020

[11] J Hu C Huiling A H Ali et al ldquoOrthogonal learning co-variance matrix for defects of grey wolf optimizer insightsbalance diversity and feature selectionrdquo Knowledge-BasedSystems vol 213 Article ID 106684 2021

[12] J E Schaufelberger and I Wipadapisut ldquoAlternate financingstrategies for build-operate-transfer projectsrdquo Journal of

Construction Engineering and Management vol 129 no 2pp 205ndash213 2003

[13] X Wang and K M Kockelman ldquoForecasting network dataspatial interpolation of traffic counts from Texas datardquoTransportation Research Record vol 1 pp 100ndash108 2105

[14] X Li H Yang J Zhang G Qian H Yu and J Cai ldquoTime-domain analysis of tamper displacement during dynamiccompaction based on automatic controlrdquo Coatings vol 11no 9 2021

[15] A Pilvere-Javorska and I Pilvere ldquoEuropean nordic countriesstock market listed companiesrsquo factor and cluster analysisapproachrdquo Emerging Science Journal vol 4 pp 443ndash4532020

[16] E R Yescombe PublicndashPrivate Partnerships Principles ofPolicy and Finance Elsevier Butterworth-Heinemann Ox-ford UK 2007

[17] J Tu ldquoEvolutionary biogeography-based Whale optimizationmethods with communication structure towards measuringthe balancerdquo Knowledge-Based Systems vol 212 Article ID106642 2020

[18] Y Bie J Ji X Wang and X Qu ldquoOptimization of electric busscheduling considering stochastic volatilities in trip traveltime and energy consumptionrdquo Computer-Aided Civil andInfrastructure Engineering vol 1 2021 in Press

[19] Y Du N Pan Z Xu F Deng Y Shen and H KangldquoPavement distress detection and classification based onYOLO networkrdquo International Journal of Pavement Engi-neering vol 1 pp 1ndash14 2020

[20] S Gatti Project Finance in 7eory and Practice DesigningStructuring and Financing Private and Public Projects Aca-demic Press Cambridge MA USA 2013

[21] H Chen A H Ali C Huiling W Mingjing P Zhifang andH G Amir ldquoMulti-population differential evolution-assistedHarris hawks optimization framework and case studiesrdquoFuture Generation Computer Systems vol 111 pp 175ndash1982020

[22] C Zhang A Ali and L Sun ldquoInvestigation on low-costfriction-based isolation systems for masonry building struc-tures experimental and numerical studiesrdquo EngineeringStructures vol 243 Article ID 112645 2021

[23] L Hoffman 7e Law and Business of International ProjectFinance A Resource for Governments Sponsors LendersLawyers and Project Cambridge University Press Cam-bridge UK 2nd edition 2001

[24] W Zhou J Liu J Lei L Yu and J-N Hwang ldquoGMNetgraded-feature multilabel-learning network for RGB-thermalurban scene semantic segmentationrdquo IEEE Transactions onImage Processing 2021

[25] H K Young YYi Chih and C William Ibbs ldquoTowards acomprehensive understanding of public private partnershipsfor infrastructure developmentrdquo California ManagementReview vol 51 2011

[26] M Wang and H Chen ldquoChaotic multi-swarm whale opti-mizer boosted support vector machine for medical diagnosisrdquoApplied Soft Computing vol 88 Article ID 105946 2020

[27] H DeAngelo and L DeAngelo ldquoCapital structure payoutpolicy and financial flexibilityrdquo Marshall School of BusinessUniversity of Southern California Los Angeles CA USA2006 httpssrncomabstract=916093 Working Paper NoFBE 02-06

[28] X Zhao X Zhang Z-N Cai et al ldquoChaos enhanced grey wolfoptimization wrapped ELM for diagnosis of paraquat-poi-soned patientsrdquo Computational Biology and Chemistryvol 78 pp 481ndash490 2019


[29] Y Zhang ldquoBoosted binary Harris hawks optimizer and fea-ture selectionrdquo Engineering with Computers vol 25 p 262020a

[30] Y Zhang ldquoTowards augmented kernel extreme learningmodels for bankruptcy prediction algorithmic behavior andcomprehensive analysisrdquo Neurocomputing vol 430 2020

[31] D Zhao L Lei Yu Fanhua et al ldquoChaotic random spare antcolony optimization for multi-threshold image segmentationof 2D Kapur entropyrdquo Knowledge-Based Systems vol 216Article ID 106510 2020

[32] C Yu C Mengxiang C Kai et al ldquoSGOA annealing-behavedgrasshopper optimizer for global tasksrdquo Engineering withComputers vol 1 pp 1ndash28 2021

[33] Y Xu C Huiling L Jie Z Qian J Shan and Z XiaoqinldquoEnhanced Moth-flame optimizer with mutation strategy forglobal optimizationrdquo Information Sciences vol 492 pp 181ndash203 2019

[34] X Zhao Li Daoliang Y Wenzhu and C Guifen ldquoFeatureselection based on improved ant colony optimization foronline detection of foreign fiber in cottonrdquo Applied SoftComputing vol 24 pp 585ndash596 2014

[35] W Shan ldquoDouble adaptive weights for stabilization of mothflame optimizer balance analysis engineering cases andmedical diagnosisrdquo Knowledge-Based Systems vol 214 Ar-ticle ID 106728 2020

[36] H Yu Li Wenshu C Chengcheng et al ldquoDynamic Gaussianbare-bones fruit fly optimizers with abandonment mecha-nism method and analysisrdquo Engineering with Computersvol 1 pp 1ndash29 2020

[37] S Kolbadi S Mohammad M Safi et al ldquoExplosive perfor-mance assessment of buried steel pipelinerdquo Advances in CivilEngineering vol 2021 Article ID 6638867 24 pages 2021

[38] S Kolbadi S Mohammad H Piri K Ali S M S Kolbadiand M Mirtaheri Seismic performance evaluation of slotted-web and bolt-flange plate moment connectionrdquo Earthquakesand Structures vol 20 no 6 pp 655ndash667 2021

[39] MMirtaheri M Salkhordeh S M S Kolbadi H Mirzaeefardand M R Razzaghian ldquoEvaluation of 2D concentricallybraced frames with cylindrical dampers subjected to near-fieldearthquake ground motionsrdquo Numerical Methods in CivilEngineering vol 4 no 3 pp 21ndash30 2020


necessary for uplifting the standards of living of the citizensand hence eradication of poverty [8]

Optimization of the Public-Private Partnership (PPP)strategies for private bidders to ensure the economic jus-tification of the investment [9] Optimization of the capitalstructure has been a concern for financial designers duringdecades Although the topics of financial theory have fullyexplored how to optimize the capital structure in corporatefinance [10] (us the challenge of infrastructure capitalstructuring is based on a combination of financial instru-ments pillars including stock debt and mezzanine capital[11] In freeway projects toll revenues are the main source ofrepayment of project loans and debts distribution of projectshares and the financing for all operations and maintenanceof freeway facilities [12] (us an accurate and reliableestimation of traffic demand and a reduction of an effectivedemand risk are two vital activities that must be consideredto achieve successful implementation of public-privatefreeway participation projects [13] (ere are many quan-titative methods to assess demand risk on toll roadshowever none of proposed methods have considered acomprehensive method for calculating user behaviours suchas population-based behaviours and socio-economic be-haviours travel expenses freeway communication andnetwork efficiency and the level of free service None ofthese methods have considered the effect of agents on eachother and cause and effect relationships between differentagents Demand forecasting and traffic analysis in tollfreeway projects should be examined more thoroughly toconsider the actual path-choosing behaviours interactionsbetween different agents and their cause and effect rela-tionships [14] (e basic options or sources available forfinancing infrastructure development include public fi-nancing development assistance or grants from donorsprivate sector financing (by private project developers)borrowing from financing institutions (multilateral inter-national regional and local) and from internally generatedfunds by operating institutions [15]

11 Literature review To design the financing to determinethe amount of project financing as a partner brought and therest of the resources required for the project as borrowing(the range of tools is shown in Figure 1) [16] Projectborrowing refers to funds lent to the executing firm by fi-nanciers such as commercial banks insurance companiesand retirement funds as well as international institutions[17] (ese loans are secured by project-related assets [18]Lenders receive the principal and interest of their loansunder any circumstances whether the company makes aprofit or a loss [19] However to ensure that there is asufficient and strong financial capacity to repay projectborrowings lenders carefully monitor projected cash flowOften a special form of financing called quasi-capital is usedto attract risk-averse investors For this purpose a specialtype of company stock is issued called preferred stockPaying preferred stockholders takes precedence over ordi-nary stockholders but is higher than those sought by projectfinanciers and other creditors of the company [20]

(is group which itself has different forms is calledMezzanine Finance A project may use other tools such asleasing addition to borrowing methods partnersrsquo contri-bution and combined financing Leasing is more practical insome countries [21] Loan terms vary from bank to bank andborrower to borrower [22] Loans may have floatingfixedinterest rates [23] Partnersrsquo contributionmay be financed byproject investors investment funds international institu-tions domestic and foreign institutional investors (such asretirement funds) or the issuance of company shares indomesticforeign stock markets (Figure 2)

(e investment pyramid is a visual description of theprinciples by which investors should arrange their invest-ment portfolio so that each amount of money invested has adifferent level of risk [24] In this regard the largest amountof money invested should have the least risk and a small partof the money should be invested in high risk assets (isprinciple ensures that peoplersquos investments do not fluctuatesharply during shocks and market downturns (e foun-dation of a pyramid investment includes secure and highlyliquid investments such as savings accounts or short-termdeposit certificates [25] Security and easy access to thisinvestment can be considered as high returns higher riskinvestments and lower liquidity However having such abase amount of available and available investments meansthat investors can quickly turn their investments into moneywhen faced with unexpected costs (is prevents the sale oflong-term investments or investments with low liquidity andcreates costs for the investor (Figure 3)

(e issue of how companies select and adjust theirfinancial resources has been the focus of many financialeconomists for a long time and is still the subject of muchdebate [26] Of course once it was believed that the natureof such issues is so complex that it is not possible toformulate a reasonable theory at this time About half acentury ago opened the debate over the possibility offormulating such theories and eventually the continuationof such debates led (Figure 4) Studies show that since thepublication of their article various theories and modelshave been expressed as the capital structure of companiesand how to choose it [26] For information about relatedtheories and patterns see Harris and Raviorsquos valuableextensive work However research shows the agentsinfluencing the capital structure of companies and providea definitive answer to the following question Why does anumber of companies choose the option of issuing sharessome of them use of internal resources and others themethod of borrowing for their financing activities in dif-ferent circumstances [27 28]

Concessionary financeGuarantees Expert credits

Commercial lendingFinance

Figure 1 Range of financial instruments






Bank Debt

Corporate bonds


Preferredsecurities


Growth and Income

Income





of risk

Increase

d Safet

y of P

rincip

al

Increased Risk




Civil worksServices



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Projectsystem

Generalenvironment


Forces

InternationalForces

PoliticalForces

TechnologicalForces


Government


Creditors


Employees












Assignmentrules







Basic level



Networkpresentation











management

design

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execution

monitoring

optimization


Asset based loans

Senior secured dept


Subordinated dept

Preferred equity

Common equity





Qτk 1113944

T

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PMj

Kτk

(1)

Sτk 1113944

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jτk


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1113936 LE middot CiP1113872 1113873 + Qτk

(2)

Max 1113944T

τk

PMj1113872 1113873

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⎪⎩

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i0aipi EBIT τkk( )1113874 1113875 (4)

1113954a i1Z 1113944Z


2

(5)

NPVOptL

OptE L

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(6)

4 Conclusion


Fina

ncia

l var

iabl

es

Dependentvariables

Independentvariable

Control variable



Data Availability




Acknowledgments


References















































Bank Debt

Corporate bonds


Preferredsecurities


Growth and Income

Income





of risk

Increase

d Safet

y of P

rincip

al

Increased Risk




Civil worksServices



BOTDBO



Projectsystem

Generalenvironment


Forces

InternationalForces

PoliticalForces

TechnologicalForces


Government


Creditors


Employees












Assignmentrules







Basic level



Networkpresentation











management

design

modeling

execution

monitoring

optimization


Asset based loans

Senior secured dept


Subordinated dept

Preferred equity

Common equity





Qτk 1113944

T

jτk

PMj

Kτk

(1)

Sτk 1113944

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jτk


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1113936 LE middot CiP1113872 1113873 + Qτk

(2)

Max 1113944T

τk

PMj1113872 1113873

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⎫⎪⎬

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1113960 1113961 1113944infin

i0aipi EBIT τkk( )1113874 1113875 (4)

1113954a i1Z 1113944Z


2

(5)

NPVOptL

OptE L

OptD L



(6)

4 Conclusion


Fina

ncia

l var

iabl

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Dependentvariables

Independentvariable

Control variable



Data Availability




Acknowledgments


References




















































Assignmentrules







Basic level



Networkpresentation











management

design

modeling

execution

monitoring

optimization


Asset based loans

Senior secured dept


Subordinated dept

Preferred equity

Common equity





Qτk 1113944

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jτk

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Sτk 1113944

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1113936 LE middot CiP1113872 1113873 + Qτk

(2)

Max 1113944T

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PMj1113872 1113873

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1113960 1113961 1113944infin

i0aipi EBIT τkk( )1113874 1113875 (4)

1113954a i1Z 1113944Z


2

(5)

NPVOptL

OptE L

OptD L



(6)

4 Conclusion


Fina

ncia

l var

iabl

es

Dependentvariables

Independentvariable

Control variable



Data Availability




Acknowledgments


References














































Basic level



Networkpresentation











management

design

modeling

execution

monitoring

optimization


Asset based loans

Senior secured dept


Subordinated dept

Preferred equity

Common equity





Qτk 1113944

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jτk

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Kτk

(1)

Sτk 1113944

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Max 1113944T

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1113960 1113961 1113944infin

i0aipi EBIT τkk( )1113874 1113875 (4)

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2

(5)

NPVOptL

OptE L

OptD L



(6)

4 Conclusion


Fina

ncia

l var

iabl

es

Dependentvariables

Independentvariable

Control variable



Data Availability




Acknowledgments


References













































Qτk 1113944

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jτk

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Kτk

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Sτk 1113944

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jτk


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1113936 LE middot CiP1113872 1113873 + Qτk

(2)

Max 1113944T

τk

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⎧⎪⎨

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1113960 1113961 1113944infin

i0aipi EBIT τkk( )1113874 1113875 (4)

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2

(5)

NPVOptL

OptE L

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(6)

4 Conclusion


Fina

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l var

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es

Dependentvariables

Independentvariable

Control variable



Data Availability




Acknowledgments


References











































Data Availability




Acknowledgments


References











































transportationinfrastructureprojectfinancing;highways

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