References

Aarts, E., Korst, J., van Laarhoven, P. (1997). Simulated annealing. In: Aarts and Lenstra (1997), pp. 91-120.

Aarts, E., Lenstra, J . (Eds.) (1997). Local Search in combinatorial Optimization. John Wiley & Sons.

Alander, J. (1999). An indexed bibliography of genetic algorithm implementations. Tech. Rep. 94-1-IMPLE, University of Vaasa.

Alvarenga, G., Mateus, G., de Tomi, G. (2003). Finding near optimal solutions for vehicle routing problems with time windows using hybrid genetic algorithm. Tech. rep., Manuscript presented at Odysseus 2003 Conference.

Angelelli, E., Mansini, R. (2002). The vehicle routing problem with time windows and simultaneous pick-up and delivery. In: Klose, A., Speranza, M. G., van Wassenhove, L. (Eds.), Quantitative Approaches o Distribution Logistics and Supply Chain Management. No. 519 in Lecture Notes in Economics and Math- ematical Systems. Springer, pp. 249-267.

Arendt, M., Achermann, Y. (2002). Aggregierte Verkehrsprognosen Schweiz und EU - Zusammenstellung vorhandener Prognosen bis 2020. Tech. rep., Bundesamt fiir Raumentwicklung.

Back, T. , Fogel, D., Michalewicz, Z. (Eds.) (2000a). Evolutionary Computation 1 - Basic Algorithms and Operators. Institute of Physics Publishing.

Back, T., Fogel, D., Michalewicz, Z. (Eds.) (2000b). Evolutionary Computation 2 - Advanced Algorithms and Operators. Institute of Physics Publishing.

Baker, B., Ayechew, M. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research 30, 787-800.

Beasley, D. (2000). Possible applications of evolutionary computation. In: Back et al. (2000a), pp. 4-19.

Beasley, D., Bull, D., Martin, R. (1993). Reducing epistasis in combinatorial prob- lems by expansive coding. In: Forrest, S. (Ed.), Proceeding of the Fifth Intern* tional Conference on Genetic Algorithms. Morgan Kaufmann.

Berger, J., Barkaoui, M. (2002). A memetic algorithms for the vehicle routing prob- lem with time windows. In: Proceedings of 7th International Command and Control Reserach and Technology Symposium.

154 References

Bierwirth, C., Mattfeld, D., Kopfer, H. (1996). On permutation representations for scheduling problems. In: Ebeling, W., Rechenberg, I., Schwefel, H., Voigt, H. (Eds.), Proceedings of Parallel Problem Solving from Nature IV. Springer-Verlag.

Blanton, J., Wainwright, R. (1993). Multi vehicle routing with time and capac- ity constraints using genetic algorithms. In: Forrest, S. (Ed.), Proceedings of the Fifth International Conference On Genetic Algorithms. Morgan Kaufmann Publishers, Inc.

Blum, C., Roli, A. (2001). Metaheuristics in combinatorial optimization: Overview and conceptual comparison. Tech. Rep. TR/IRIDIA/2001-3, IRIDIA.

Braysy, 0 . (2001). Genetic algorithms for the vehicle routing problem with time windows. Arpakannus 1, 33-38.

Burke, E., Newall, J., Weare, R. (1996). A memetic algorithm for university exam timetabling. In: Burke, E., Ross, P. (Eds.), Proceedings of First International Conference of Practice and Theory of Automated Timetabling. Vol. 1153 of Lecture Notes in Computer Science. Springer.

Butt, S., Cavalier, T. (1994). A heuristic for the multiple tour maximum collection problem. Computers & Operations Research 21 (I), 101-111.

Butt, S., Ryan, D. (1999). An optimal solution procedure for the multiple tour maximum collection problem using column generation. Computers & Operations Research 26, 427441.

Casco, D., Golden, B., Wasil, E. (1988). Vehicle routing with backhauls: Models, algorithms and case studies. In: Golden and Assad (1988), pp. 127-147.

Chao, I.-M., Golden, B., Wasil, E. (1996). The team orienteering problem. European Journal of Operational Research 88, 464-474.

Christofides, N. (1990). Vehicle routing. In: E.L. Lawler et al. (1990), pp. 431-448. Cloonan, J. (1966). A heuristic approach to some sales territory problems. In: Hertz,

D., Melese, J. (Eds.), Proceedings of the Fourth International Conference on Operational Research. Wiley-Interscience.

Coello, C. C. (2002). Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Computational met hods in applied mechanics and engineering 191, 1245-1287.

Coit, D., Smith, A., Tate, D. (1996). Adaptive penalty methods for genetic optimiza- tion of constrained combinatorial problems. INFORMS Journal on Computing 8 (2), 173-182.

Cordeau, J.-F., Laporte, G. (2003). A tabu search heuristic for the static multi- vehicle dial-a-ride-problem. Transportation Research Part B 37, 579-594.

Crainic, T. (2000). Service network design in freight transportation. European Jour- nal of Operational Research 122, 272-288.

Crainic, T . (2003). Handbook of Transportation Science, 2nd Edition. Kluwer, Ch. Long-haul Freight Transportation, pp. 451-516.

Crainic, T., Laporte, G. (1997). Planning models for freight transportation. Euro- pean Journal of Operational Research 97, 409-438.

Daganzo, C. (1999). Logistic System Analysis, 3rd Edition. Springer. de Queir6s Vieira Martins, E., Pascoal, M. B., Rasteiro, D. L. D., dos Santos, J.

(1999). The optimal path problem. Investiga@o Operacional 19, 43-60. Desrosiers, J., Dumas, Y., Soumis, F. (1998). The multi vehicle dial-a-ride prob-

lem. In: Daduna, J., Wren, A. (Eds.), Proceedings of Computer-Aided Transit Scheduling. Vol. 308 of Lecture Notes in Economics and Mathematical System.

References 155

Dethloff, J . (1994). Verallgemeinerte Tourenplanungsprobleme. Ph.D. thesis, Uni- versitat Hamburg.

Diaby, M., Ramesh, R. (1995). The distribution problem with carrier service: A dual based penalty approach. ORSA Journal on Computing 7 ( I ) , 24-35.

Doerner, K., Hartl, R., Reimann, M. (2000). Ants solve time constraint pickup and delivery problems with full truckloads. In: Fleischmann, B., Lasch, R., Derigs, U., Domschke, W., Rieder, U. (Eds.) , Operations Research Proceedings 2000. Springer, pp. 395-400.

Domenjoud, E., Kirchner, C., Zhou, J . (1998). Generating feasible schedules for a pick-up and delivery problem. In: Proceedings of the 4th International Confer- ence of Principles and Practice of Constraint Programming. Vol. 1520 of Lecture Notes in Computer Science.

Domschke, W. (1985). Logistik: Rundreisen und Touren, 2nd Edition. Oldenbourg. Dorigo, M., Caro, G. D., Gambardella, L. (1999). Ant algorithms for discrete opti-

mization. Artificial Life 5 (2), 137-172. Dowsland, K. (19%). Simulated annealing. In: Reeves (l993), pp. 20-69. Duhamel, C., Potvin, J., Rousseau, J . (1997). A tabu search heuristic for the vehi-

cle routing problem with backhauls and time windows. Transportation Science 31 ( I ) , 49-59.

Dumas, Y., Desrosiers, J., Soumis, F. (1991). The pickup and delivery problem with time windows. European Journal of Operational Research 54, 7-22.

E.L. Lawler, J.K. Lenstra, A.H.G. Rinnooy Kan, D.B. Shmoys (Eds.) (1990). The Traveling Salesman Problem, 4th Edition. Wiley Interscience.

Erkens, E. (1998). Kostenbasierte Tourenplanung im Straengiiterverkehr. Ph.D. the- sis, Universitat Bremen.

Erkut, E., Zhang, J. (1996). The maximum collection problem with time-dependent rewards. Naval Research Logistics 43, 749-763.

Eshelman, L. (2000). Genetic algorithms. In: Back et al. (2000a), pp. 64-80. European Commission (2001). White paper - european transport policy for 2010:

time to decide. Eurostat (2002). The eu energy and transport in figures. statistical pocket book. Feillet, D., Dejax, P., Gendreau, M. (2001). The selective traveling salesman problem

and extensions: An overview. Tech. Rep. CRT-2001-25, CRT. Fenn, M. (Ed.) (2004). Transportation Statistics Annual Report. U. S. Department

of Transportation Bureau of Transportation Statistics. Fiat, A., Woeginger, G. (Eds.) (1998). Online Algorithms. Vol. 1442 of Lecture Notes

in Computer Science. Springer. Fleischmann, B. (1998). Design of freight traffic networks. In: Fleischmann, B., van

Nunen, J., Speranza, M. G., Stahly, P. (Eds.), Advances in Distribution Logistics. Springer, pp. 55-81.

Fleischmann, B., Gnutzmann, S., SandvoB, E. (2003). Dynamic vehicle routing based on on-line traffic information. to appear in Transportation Science .

Fogel, D. (2000). Introduction to evolutionary computation. In: Back et al. (2000a), pp. 1-3.

Frantzeskakis, L., Powell, W. (1990). A successive linear approximation procedure for stochastic, dynamic vehicle allocation problems. Transportation Science 24 ( I ) , 40-57.

156 References

Gambardella, L., Taillard, E., Agazzi, G. (1999). Macs-vrptw: A multiple ant colony system for vehcle routing problems with time windows. Tech. Rep. IDSIA-06-99, IDSIA.

Gendreau, M., Laporte, G., Semet, F. (1998). A branch-and-cut algorithm for the undirected selective traveling salesman problem. Networks 32 (4), 263-279.

Gensch, D. (1978). An industrial application of the traveling salesman's subtour problem. AIIE Transactions 10 (4), 362-370.

Ghiani, G., Guerriero, F., Laporte, G., Musmanno, R. (2003). Real-time vehicle rout­ing: Solution concepts, algorithms and parallel computing strategies. European Journal of Operational Research 151, 1-11.

Glover, F., Laguna, M. (1993). Tabu search. In: Reeves (1993), pp. 70-150. Goldberg, D. (1989). Genetic Algorithm in Search, Optimization & Machine Learn­

ing. Addison Wesley Publishing Company. Golden, B., Assad, A. (Eds.) (1988). Vehicle Routing: Methods and Studies. Elsevier

Science Publishers B.V. Golden, B., Assad, A., Dahl, R. (1984). Analysis of a large scale vehicle routing

problem with an inventory component. Large Scale Systems 7, 181-190. Golden, B., Levy, L., Dahl, R. (1981). Two generalizations of the traveling salesman

problem. OMEGA 9 (4), 439-441. Golden, B., Stewart, W. (1985). Empirical analysis of heuristics. In: E.L. Lawler

et al. (1990), pp. 207-249. Gomber, P., Schmidt, C., Weinhardt, C. (1997). Elektronische Markte fiir dezentrale

Transportplanung. Wirtschaftsinformatik 39 (2), 137-145. Greb, T. (1998). Interaktive Tourenplanung mit Tabu Search. Ph.D. thesis, Univer-

sitt Bremen. Griinert, T., Sebastian, H.-J. (2000). Planning models for long-haul operations of

postal and express shipment companies. European Journal of Operational Re­search 122, 289-309.

Kerry, M. (2001). Transportpreise und Transportkosten der verschiedenen Verkehrstrager im Giiterverkehr. Tech. Rep. 14, Kammer fur Arbeiter und Angestellte, Abt. Umwelt und Verkehr.

Hertz, A., Taillard, E., de Werra, D. (1997). Tabu search. In: Aarts and Lenstra (1997), pp. 121-136.

Ibaraki, T. (1997). Combination with local search. In: Back, T., Fogel, D., Michael-wicz, Z. (Eds.), Handbook of Evolutionary Computation. Institute of Physics Publishing, p. D3.2.

IGF (Ed.) (2002). Economic Effects of Transportation: The Freight Story. ICF Con­sulting.

Joines, J., Kay, M. (2002). Utilizing hybrid genetic algorithms. In: Sarker et al. (2002), pp. 199-228.

Kilger, C , Renter, B. (2002). Collaborative planning. In: Stadtler, H., Kilger, C. (Eds.), Supply Chain Management and Advanced Planning. Springer, pp. 223-237.

Kopfer, H. (1984). Losung des Frachtoptimierungsproblems im gewerblichen Giiterfernverkehr - Losungsaufwand versus Losungsqualitat. Ph.D. thesis, Uni-versitat Bremen.

Kopfer, H. (1989). Heuristische Suche in Operations Research und Kiinstlicher Intel-ligenz - Strategien des heuristischen Problemlosens und die Losung betrieblicher Dispositionsprobleme. Habilitationsschrift.

References 157

Kopfer, H. (1992). Konzepte genetischer Algorithmen und ihre Anwendung auf das Frachtoptimierungsproblem im gewerblichen Guterfernverkehr. OR Spektrum 14, 137-147.

Kopfer, H., Pankratz, G. (1998). Das Groupage-Problem kooperierender Verkehrstrager. In: Kall, P., Luthi, J.- J . (Eds.) , Operations Research Proceedings 1998.

Kopfer, H., Pankratz, G., Erkens, E. (1994). Entwicklung eines hybriden Genetischen Algorithmus zur Tourenplanung. OR Spektrum 16, 21-31.

Laporte, G., Martello, S. (1990). The selective travelling salesman problem. Discrete Applied Mathematics 26.

Larsen, J. (2001). Parallelization of the vehicle routing problem with time windows. Ph.D. thesis, University of Copenhagen.

Lau, H., Liang, Z. (2001). Pickup and delivery with time windows: Algorithms and test case generation. In: Proceedings of the IEEE Conference on Tools with Artificial Intelligence (ICTAI) .

Li, H., Lim, A. (2001). A mataheuristic for the pickup and delivery problem with time windows. In: proceedings of the 13th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'Ol).

Machado, P., Tavares, J . , Pereira, F., Costa, E. (2002). Vehicle routing problem: Doing it the evolutionary way. In: Proceedings on the Genetic and Evoloutionary Computation Conference. Morgan Kaufmann, Inc.

Mattfeld, D. (1996). Evolutionary Search and the Job Shop. Physica-Verlag. Meier-Sieden, M. (1978). Die Auftragsauswahl in Betrieben des Gelegen-

heitsverkehrs. Vol. 22 of Verkehrswissenschaftliche Studien. Vandenhoeck & Ruprecht in Gottingen.

Merz, P., Freisleben, B. (2001). Memetic algorithms for the traveling salesman prob- lem. Complex Systems 13 (4), 297-345.

Michaelewicz, Z. (1996). Genetic Algorithms + Data Structures = Evolution Pro- grams, 3rd Edition. Springer.

Michaelewicz, Z. (2000). Constraint-preserving operators. In: Back et al. (2000b), pp. 62-68.

Michalewicz, Z. (2000a). Decoders. In: Back et al. (2000b), pp. 49-55. Michalewicz, Z. (2000b). Repair algorithms. In: Back et al. (2000b), pp. 56-61. Millar, H. (1996). Planning fish scouting activity in industrial fishing. Fisheries Re-

search 25, 63-75. Millar, H., Kiragu, M. (1997). A time-based formulation and upper bounding scheme

for the selective travelling salesperson problem. Journal of the Operational Re- search Society 48, 511-518.

MitroviC-MiniC, S. (1998). Pickup and delivery problems with time windows: A sur- vey. Tech. Rep. SFU CMPT T R 1998-12, Simon Fraser University.

Moore, C. (Ed.) (2004). National Transportation Statistics 2003. U.S. Department of Transportation Bureau of Transportation Statistics.

Moore, W. (Ed.) (2002). Freight Shipments in America. U.S. Department of Trans- portation Bureau of Transportation Statistics.

Moscato, P. (1989). On evolution, search, optimization, genetic algorithms and mar- tial arts: Towards memetic algorithms. Tech. Rep. 790, Caltech Concurrent Com- putation Program, California Institute of Technology.

158 References

Nanry, W., Barnes, J . (2000). Solving the pickup and delivery problem with time windows using reactive tabu search. Transportation Research Part B 34, 107- 121.

Nash, C., Niskanen, E. (2003). Experiences in road pricing in europe - re- view of research and practice. In: Proceedings of TRIP research confer- ence: The Economic and Environmental Consequences of Regulating Traffic. www.akf.dk/trip/konference03/papers/niskanen-nash.pdf, 25.06.2003.

Naudts, B., Suys, D., Verschoren, A. (1997). Epistasis as a basic concept in formal landscape analysis. In: Back, T . (Ed.), Proceedings of the Seventh International Conference on Genetic Algorithms. Morgan Kaufmann.

Nemhauser, G., Wolsey, L. (1988). Integer and Combinatorial Optimization. Wiley. Oberhausen, J . (2003). Trends in road freight transport 1990-2001. Tech. rep., Eu-

rostat. Ochi, L., Vianna, D., Drummond, L., Victor, A. (1998). A parallel evolutionary algo-

rithm for the vehicle routing problem with heterogeneous fleet. In: Proceedings of IPPS/SPDP Workshops 1998.

Pankratz, G. (2002). Dynamische speditionelle Transportdisposition unter beson- derer Beriicksichtigung der Fremdvergabe. Ph.D. thesis, FernUniversitat- Gesamthochschule Hagen.

Pekny, J., Miller, D. (1990). An exact algorithm for the resource constrained travel- ing salesman problem with application to scheduling with an aggregate deadline. In: Eighteenth Annual Computer Science Conference. ACM.

Pereira, F., Tavares, J., Machado, P., Costa, E. (2002). GVR: a new genetic rep- resentation for the vehicle routing problem. In: Proceedings of the 13th Irish Conference on Artificial Intelligence and Cognitive Science AICS2002.

Porto, V. (2000). Evolutionary programming. In: Back et al. (2000a), pp. 89-102. Potvin, J.-Y., Bengio, S. (1996). The vehicle routing problem with time windows

part ii: Genetic search. INFORMS Journal on Computing 8 (2), 165-172. Powell, W., Sheffi, Y., Nickerson, K., Butterbraugh, K., Atherton, S. (1988). Maxi-

mizing profits for north american van lines' truckload division: A new framework for pricing and operations. Interfaces 18 (I) , 21-41.

Powell, W., Snow, W., Cheung, R.-M. (2000). Adaptive labeling algorithms for the dynamic assignment problem. Transportation Science 34 (I) , 67-85.

Psaraftis, H. (1983). An exact algorithm for the single vehicle many-to-many dial- a-ride problem with time windows. Transportation Science 17 (3), 351-357.

Psaraftis, H. (1995). Dynamic vehicle routing: Status and prospects. Annals of Op- erations Research 61.

Psaraftis, H. N. (1988). Dynamic vehicle routing problems. In: Golden and Assad (1988), pp. 223-248.

Punakivi, M., Yrjola, H., Holmstrom, J. (2001). Solving the last mile issue: Reception box or delivery box? International Journal of Physical Distribution and Logistics Management 31 (6), 427-439.

Reeves, C. (Ed.) (1993). Modern Heuristic Techniques for Combinatorial Problems. Blackwell Scientific Publications.

Rego, C., Roucairol, C. (1995). Using tabu search for solving a dynamic multitermi- nal truck dispatching problem. European Journal of Operational Research 83, 411-429.

References 159

Riebel, P. (1986). Probleme einer entscheidungsorientierten Kosten-, Erlos- und Deckungsbeitragsrechnung im Guterkraftverkehr. Zeitschrift fur Verkehrswis- senschaft 57 ( I ) , 3-38.

Rodrigue, J.-P. (1999). Globalization and the synchronization of transport terminals. Journal of Transport Geography 7, 255-261.

Rothlauf, F. (2003). Redundant representations in evolutionary computation, work- ing Paper 312003.

Rudolph, G. (2000). Evolution strategies. In: Back et al. (2000a), pp. 81-88. Sandholm, T. (2002). Algorithm for optimal winner determination in combinatorial

auctions. Artificial Intelligence 135 (2), 1-54. Sarker, R., Mohammadian, M., Yao, X. (Eds.) (2002). Evolutionary Optimization.

International Series in Operations Research and Management Science. Kluwer Academic Publishers.

Sarma, J . , Jong, K. D. (2000). Generation gab methods. In: Back et al. (2000a), pp. 205-211.

Savelsbergh, M., Sol, M. (1995). The general pickup and delivery problem. Trans- portation Science 29.

Savelsbergh, M., Sol, M. (1998). Drive: Dynamic routing of independent vehicles. Operations Research 46, 474-490.

Schmidt, K. (1989). Die Einzelkosten- und Deckungsbeitragsrechnung als Instrument der Erfolgskontrolle und Fahrzeugdisposition im gewerblichen Guterfernverkehr. Vol. 22 of GVB Schriftenreihe. GVB.

Schonberger, J., Kopfer, H. (2003). A memetic algorithm for a pickup and delivery selection problem. In: Proceedings of CIMCA 2003. published on CD.

Schonberger, J., Mattfeld, D., Kopfer, H. (2004). Memetic algorithm timetabling for non-commercial sport leagues. European Journal of Operational Research 153 ( I ) , 102-116.

Seuring, S. (2001). Die Produkt-Kooperations-Matrix im Supply Chain Managc ment. Tech. Rep. EcoMTex-Diskussionspapier Nr. 02, Universitat Oldenburg.

Sexton, T. , Choi, Y.-M. (1986). Pickup and delivery of partial loads with "soft" time windows. American Journal of Mathematical and Management Sciences 6 (3-4), 369-398.

Sigurd, M., Pisinger, D., Sig, M. (2000). The pickup and delivery problem with time windows and precedences. Tech. Rep. 0018, University of Copenhagen, Dept. of Computer Sciences.

Slater, A. (2002). Specification for a dynamic vehicle routing and scheduling system. International Journal of Transport Management 1, 29-40.

Smith, A., Coit, D. (2000). Penalty functions. In: Back et al. (2000b), pp. 41-48. Solomon, M. (1987). The vehicle routing and scheduling problems with tome window

constraints. Operations Research 35 (2), 254-265. Stumpf, P. (1998). Tourenplanung im speditionellen Guterfernverkehr. Vol. 37 of

GVB Schriftenreihe. GVB. Tasgetiren, M., Smith, A. (2000). A genetic algorithm for the orienteering problem.

In: Proceedings of the Congress on Evolutionary Computation. Tavares, J., Pereira, F., Machado, P., Costa, E. (2003). On the influence of gvr in

vehicle routing. In: Proceedings of the ACM Symposium on Applied Computing 2003.

160 References

Thangiah, S. (1995). Vehicle routing with time windows using genetic algorithms. In: Chambers, L. (Ed.), Applications Handbook of Genetic Algorithms: New Frontiers. CRC Press, pp. 253-278.

Thangiah, S., Vinayagamoorthy, R., Gubbi, A. (1995). Vehicle routing with time deadlines using genetic and local algorithms. In: Forrest, S. (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms. Morgan Kaufmann Publishers, Inc.

Toth, P., Vigo, D. (1999). A heuristic algorithm for the symmetric and asymmet- ric vehicle routing problems with backhauls. European Journal of Operational Research 113, 528-543.

Trip, J., Bontekoning, Y. (2002). Integration of small freight flows in the intermodal transport system. Journal of Transport Geography 10, 221-229.

van der Bruggen, L., Lenstra, J., Schuur, P. (1993). Variable-depth search for the single-vehicle pickup and delivery problem with time windows. Transportation Science 27 (3), 298-311.

van Laarhoven, P., Aarts, E. (1987). Simulated Annealing: Theory and Applications. Kluwer Academic Publishers.

Verweij, A., Aardal, K. (2000). The merchant subtour problem. Tech. rep., Univer- siteit Utrecht.

Vohra, R., s. de Vries (2003). Combinatorial auctions: A survey. to appear in IN- FORMS Journal on Computing 15.

Voss, S. (1993). Concepts for parallel tabu search. In: Proceedings on Symposium on Applied Mathematical Programming and Modeling (APMOD93).

Whitley, D. (2000). Permutations. In: Back et al. (2000a), pp. 139-150. Williams, H. (1993). Model Solving in Mathematical Programming, 2nd Edition.

John Wiley & Sons. Williams, H. (1999). Model Building in Mathematical Programming, 4th Edition.

John Wiley & Sons. Withley, D., Gordon, V., Mathias, K. (1994). Lamarckian evolution, the baldwin

effect and function optimization. In: Davidor, Y., Schwefel, H.-P., Manner, R. (Eds.), Proceedings of Parallel Problem Solving from Nature - PPSN 111. No. 866 in Lecture Notes in Computer Science. Springer.

Wlcek, H. (1998). Gestaltung der Giiterverkehrsnetze von Sammelgutspeditionen. No. 37 in GVB Schriftenreihe. GVB.

Yao, X. (2002). Evolutionary computation. In: Sarker et al. (2002), pp. 27-53. Zhu, K. Q. (2000). A new genetic algorithm for vrptw, working paper, National

University of Singapore. Ziegelmann, M. (2001). Constrained shortest paths and related problems. Ph.D.

thesis. Universitt des Saarlandes.

Index

adaptation, 52 adaptive penalties, 119 advanced memetic algorithm, 71 aggregation of flows, 6 alternating and converging constraint,

123 ant algorithms, 51 auction

combinatorial, 141

back-freight, 5 backward feeding, 9 baldwin effect, 63 benchmark instances, 42 biased random drawing, 84 bottleneck resource, 18 bottleneck selection, 25

capacitated vehicle routing problem, 20 carrier, 17 charge function, 21 chromosome, 55 cluster builder, 66 cluster first-route second, 69 co-evolution

of partial solutions, 75 with specialization, 74

co-evolutionary memetic algorithm, 72 collaborative planning, 136 collaborative planning approach, 142 collection, 7 combinatorial auction, 141 compulsory request, 27 consolidation strategy, 6

construction approach parallel, 78 sequential, 78

control alternating and converging con-

straints, 124 cooperation, 136 coupling savings, 18 crew scheduling, 11 crossover, 57

modified precedence preserving crossover, 88

mPPX, 88 PPX, 88 precedence preserving crossover, 88

data hull, 85 decision problem, 16 decomposition approach, 71 deferrable request, 109 delivery, 9 destination, 6 dial-a-ride-problem, 33 direct representation, 84 distribution center, 4 distribution network, 4 domain integration, 136 double ranking, 120 dynamic penalties, 118

empty balancing, 11 empty miles, 5 enonomies of scale, 4 environmental impacts, 3

162 Index

evolutionary algorithms, 52 evolutionary programming, 53 evolutionary strategies, 53

five-phase transport-process, 9 flow of goods

aggregation, 6 bi-directional, 6 uni-directional, 4

forward feeding, 8 freight carrier, 5 freight charge, 17 freight charge optimization, 22 freight charge optimization problem, 22,

34 freight tariff function, 34 freight transport network, 7 fulfillment costs, 12 fulfilment mode, 17 full truckload problem, 33

gene, 55 genetic algorithm, 53 genetic clustering, 68 genetic local search, 63 genetic sectoring, 69 genetic sequencing, 65 genetic vehicle representation, 73 genotype, 55 groupage system, 135

heuristic, 50 heuristic algorithms, 20 heuristics

meta-, 20 hierarchical planning approach, 22 hill climber, 62 hub, 6 hybrid genetic search, 63

improvement approach, 50 individual, 52 inner ranking, 120 inst ant iation order, 84 itinerary, 10

lamarckian evolution, 63 less-than-truckload, 7 line haul, 8

local search methods, 50 location in networks, 9 locus, 55 logistics service provider, 17

incorporation, 19 logistics system configuration, 10 logistics system deployment, 10 logistics system design, 9

mating pool, 56 means of transport, 2 meme, 63 memetic algorithm, 63

advanced, 71 co-evolutionary, 72

meta-heuristics, 20 modal split, 2 mode

fulfilment, 17 selection, 18

mode selection problem, 19 modes of road transport

hire or reward, 3 own account, 2

multi-chromosome representation, 71 multiple traveling salesman problem, 20 mutation, 52 myopic planning, 28

network design, 9 network layout, 9

online planning problems, 41 operation, 34 optimal approaches, 20 origin, 6 overhead cost, 4

passenger-kilometer , 2 pd-path, 35 pd-schedule, 35 penalty

adaptive, 119 dynamic, 118 static, 116

penalty value, 118 performance of transport, 2 phenotype, 55 pickup, 9 pickup and delivery selection problem

Index 163

capacitated, 39 general, 36

pickup and delivery planning problems, 12

pickup and delivery problem with time windows, 33

pickup and delivery path, 35 pickup and delivery planning problem

simultaneous, 23 pickup and delivery problem, 33 pickup and delivery request, 31 pickup and delivery schedule, 35 pickup and delivery selection problem

with compulsory requests, 40 pickup and delivery selection model

simultaneous, 23 pickup and delivery selection problem

with logistics service provider incorporation, 38

with postponement, 41 planning

collaborative, 136 population, 52

model, 92 population based approaches, 50 portfolio

sub-, 22 portfolio re-composition problem, 138 postponement, 27 problem

portfolio re-composition, 138 profit contribution

maximization, 18

quote, 117 quote first-cost second, 121 quote-class, 120

rail transport, 2 ranking

double, 120 inner, 120

regional multimodal planning, 10 rejection of transport demands, 34 replenishment, 4 representation, 55

direct, 84 multi-chromosome, 71 of a pd-schedule, 84

permutation based, 65 problem specific, 72

reproduction, 52 reproduction model

(CL + A), 120 request, 31

compulsory, 27 deferrable, 109 urgent, 28

request acceptance, 16 operational, 17 problem, 16 tactical, 16

request selection, 18 requests

internal, 17 revenue, 16 road transport, 2 rolling planning horizon, 27 roulette-wheel-selection, 56 route, 19

improvement, 82 route construction heuristic, 69 route first-cluster second, 66 routes, 19

tentative, 80 routing, 19 routing problem, 19

search algorithms, 49 selection, 52

bottleneck, 25 maximal-profit , 25 with compulsory requests, 26 with postponement, 27

separation genes, 71 sequencing

genetic, 65 shared distances, 46 shipment, 4 simulated annealing, 50 simultaneous approach, 23 simultaneous construction approach, 50 simultaneous planning models

generic, 24 static penalties, 116 sub-portfolio, 22 successive approaches, 50

164 Index

tabu search, 51 third party, 5 ton-kilometer , 1 tour, 19 trail of a population, 130 trajectory methods, 50 transport process, 7 transportation plan, 12 transshipment, 6 traveling salesman problem, 20 truckload, 4

vehicle allocation problem, 33 vehicle routing and scheduling, 11 vehicle routing problem

capacitated, 20 vehicle routing problem with backhauls,

33 vehicle routing problem with time

windows, 20

waterway transport, 2