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Twenty Years of Vehicle Routing in Vienna

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Dynamic Perspectives on Managerial Decision Making

Abstract

The vehicle routing problem was formulated more than 50 years ago and has attracted great attention since then, not least due to its high practical relevance and its computational complexity. Throughout the years, various generalizations and solution techniques were proposed. The purpose of this survey is to describe the developments in this particular field. Starting with a basic model, several generalizations to the classical vehicle routing problem are explained by gradually extending the initial model. A special focus lies on the contributions to this field of study by Richard F. Hartl and his colleagues at the University of Vienna, particularly with regard to developed solution methods.

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Notes

  1. 1.

    http://prolog.univie.ac.at/research/ConVRP/

References

  • Archetti, C., Doerner, K. F., & Tricoire, F. (2013). A heuristic algorithm for the free newspaper delivery problem. European Journal of Operational Research, 230(2), 245–257.

    Article  Google Scholar 

  • Balseiro, S. R., Loiseau, I., & Ramonet, J. (2011). An ant colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows. Computers and Operations Research, 38(6), 954–966.

    Article  Google Scholar 

  • Bektas, T., Repoussis, P. P., & Tarantilis, C. D. (2014). Dynamic vehicle routing problems. Vehicle Routing: Problems, Methods, and Applications, 18, 299–347.

    Article  Google Scholar 

  • Beltrami, E. J., & Bodin, L. D. (1974). Networks and vehicle routing for municipal waste collection. Networks, 4(1), 65–94.

    Article  Google Scholar 

  • Bent, R. W., & Van Hentenryck, P. (2004). Scenario-based planning for partially dynamic vehicle routing with stochastic customers. Operations Research, 52(6), 977–987.

    Article  Google Scholar 

  • Bertazzi, L., Savelsbergh, M., & Speranza, M. (2008). Inventory routing. In B. L. Golden, S. Raghavan, & E. A. Wasil (Eds.), The vehicle routing problem: Latest advances and new challenges. Operations research/computer science interfaces series. (Vol. 43, pp. 49–72). New York: Springer US.

    Google Scholar 

  • Braekers, K., Hartl, R. F., Parragh, S. N., & Tricoire, F. (2016). A bi-objective home care scheduling problem: Analyzing the trade-off between costs and client inconvenience. European Journal of Operational Research, 248(2), 428–443.

    Article  Google Scholar 

  • Bräysy, O., & Gendreau, M. (2005a). Vehicle routing problem with time windows, Part I: Route construction and local search algorithms. Transportation Science, 39(1), 104–118.

    Article  Google Scholar 

  • Bräysy, O., & Gendreau, M. (2005b). Vehicle routing problem with time windows, Part II: Metaheuristics. Transportation Science, 39(1), 119–139.

    Article  Google Scholar 

  • Breunig, U., Schmid, V., Hartl, R. F., & Vidal, T. (2015). A fast large neighbourhood based heuristic for the two-echelon vehicle routing problem. Manuscript submitted for publication.

    Google Scholar 

  • Bullnheimer, B., Hartl, R. F., & Strauss, C. (1999a). Applying the ant system to the vehicle routing problem. In S. Voß, S. Martello, I. Osman, & C. Roucairol (Eds.), Meta-heuristics (pp. 285–296). New York: Springer US.

    Google Scholar 

  • Bullnheimer, B., Hartl, R. F., & Strauss, C. (1999b). An improved ant system algorithm for the vehicle routing problem. Annals of Operations Research, 89, 319–328.

    Article  Google Scholar 

  • Bullnheimer, B., Hartl, R. F., & Strauss, C. (1999c). A new rank based version of the ant system - a computational study. Central European Journal for Operations Research and Economics 7(1), 25–38.

    Google Scholar 

  • Caris, A., Macharis, C., & Janssens, G. K. (2013). Decision support in intermodal transport: A new research agenda. Computers in Industry, 64(2), 105–112.

    Article  Google Scholar 

  • Chao, I. M., Golden, B. L., & Wasil, E. A. (1995). An improved heuristic for the period vehicle routing problem. Networks, 26(1), 25–44.

    Article  Google Scholar 

  • Chao, I. M., Golden, B. L., & Wasil, E. A. (1996a). A fast and effective heuristic for the orienteering problem. European Journal of Operational Research, 88(3), 475–489.

    Article  Google Scholar 

  • Chao, I. M., Golden, B. L., & Wasil, E. A. (1996b). The team orienteering problem. European Journal of Operational Research, 88(3), 464–474

    Article  Google Scholar 

  • Christofides, N., & Beasley, J. E. (1984). The period routing problem. Networks, 14(2), 237–256.

    Article  Google Scholar 

  • Christofides, N., Mingozzi, A., & Toth, P. (1979). The vehicle routing problem. In N. Christofides, A. Mingozzi, P. Toth, & C. Sandi (Eds.), Combinatorial optimization (pp. 315–338). Chichester: Wiley.

    Google Scholar 

  • Clarke, G., & Wright, J. W. (1964). Scheduling of vehicles from a central depot to a number of delivery points. Operations Research, 12(4), 568–581.

    Article  Google Scholar 

  • Cordeau, J. F. (2006). A branch-and-cut algorithm for the dial-a-ride problem. Operations Research, 54(3), 573–586.

    Article  Google Scholar 

  • Cordeau, J. F., Gendreau, M., & Laporte, G. (1997). A tabu search heuristic for periodic and multi-depot vehicle routing problems. Networks, 30(2), 105–119.

    Article  Google Scholar 

  • Cordeau, J. F., & Laporte, G. (2003). A tabu search heuristic for the static multi-vehicle dial-a-ride problem. Transportation Research Part B: Methodological, 37(6), 579–594.

    Article  Google Scholar 

  • Cordeau, J. F., Laporte, G., & Mercier, A., et al. (2001). A unified tabu search heuristic for vehicle routing problems with time windows. Journal of the Operational Research Society, 52(8), 928–936.

    Google Scholar 

  • Crevier, B., Cordeau, J. F., & Laporte, G. (2007). The multi-depot vehicle routing problem with inter-depot routes. European Journal of Operational Research, 176(2), 756–773.

    Article  Google Scholar 

  • Current. J. R. (1981) Multiobjective design of transportation networks. Ph. D. thesis, The Johns Hopkins University.

    Google Scholar 

  • Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management Science, 6, 80–91.

    Article  Google Scholar 

  • Dawid, H., Doerner, K. F., Hartl, R. F., Reimann, M. (2002). Ant systems to solve operational problems. In H. Dawid, K. F. Doerner, G. Dorffner, T. Fent, M, Feurstein, R. F. Hartl, M. Mild, M. Natter, M. Reimann, & A. Taudes (Eds.), Quantitative models of learning organizations. Interdisciplinary studies in economics and management (pp. 63–94). Vienna: Springer Vienna.

    Google Scholar 

  • Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182–197.

    Article  Google Scholar 

  • Desaulniers, G., Madsen, O. B. G., & Røpke, S. (2014). The vehicle routing problem with time windows. In P. Toth & D. Vigo (Eds.), Vehicle routing: Problems, methods, and applications (2nd ed.). MOS - SIAM series on optimization (pp. 119–160). Philadelphia: SIAM - Society for Industrial and Applied Mathematics.

    Chapter  Google Scholar 

  • Doerner, K. F., Fuellerer, G., Hartl, R. F., Gronalt, M., & Iori, M. (2007). Metaheuristics for the vehicle routing problem with loading constraints. Networks, 49(4), 294–307.

    Article  Google Scholar 

  • Doerner, K. F., Gronalt, M., Hartl, R. F., Kiechle, G., & Reimann, M. (2008a). Exact and heuristic algorithms for the vehicle routing problem with multiple interdependent time windows. Computers & Operations Research, 35(9), 3034–3048.

    Article  Google Scholar 

  • Doerner, K. F., Gronalt, M., Hartl, R. F., Reimann, M., Strauss, C., & Stummer, M. (2002). Savingsants for the vehicle routing problem. In S. Cagnoni, J. Gottlieb, E. Hart, M. Middendorf, & G. Raidl (Eds.), Applications of evolutionary computing. Lecture notes in computer science. (Vol. 2279, pp. 11–20). Berlin: Springer.

    Google Scholar 

  • Doerner, K. F., Gutjahr, W. J., Hartl, R. F., & Lulli, G. (2008b) Stochastic local search procedures for the probabilistic two-day vehicle routing problem. In A. Fink, & F. Rothlauf (Eds.), Advances in computational intelligence in transport, logistics, and supply chain management. Studies in computational intelligence (Vol. 144, pp. 153–168). Berlin: Springer.

    Google Scholar 

  • Doerner, K. F., & Hartl, R. F. (2008). Health care logistics, emergency preparedness, and disaster relief: New challenges for routing problems with a focus on the Austrian situation. In B. L. Golden, S. Raghavan, & E. A. Wasil (Eds.), The vehicle routing problem: Latest advances and new challenges. Operations research/computer science interfaces (Vol. 43, pp. 527–550). New York: Springer US.

    Google Scholar 

  • Doerner, K. F., Hartl, R. F., Benkner, S., & Lucka, M. (2006). Parallel cooperative savings based ant colony optimization - multiple search and decomposition approaches. Parallel Processing Letters, 16(3), 351–369.

    Article  Google Scholar 

  • Doerner, K. F., Hartl, R. F., Kiechle, G., Lucka, M., & Reimann, M. (2004). Parallel ant systems for the capacitated vehicle routing problem. In J. Gottlieb & G. Raidl (Eds.), Evolutionary computation in combinatorial optimization. Lecture notes in computer science (Vol. 3004, pp. 72–83). Berlin: Springer.

    Google Scholar 

  • Doerner, K. F., Hartl, R. F., & Lucka, M. (2005). A parallel version of the D-Ant algorithm for the vehicle routing problem. Parallel Numerics, 5, 109–118.

    Google Scholar 

  • Doerner, K. F., Hartl, R. F., & Reimann, M. (2001). Cooperative ant colonies for optimizing resource allocation in transportation. In E. Boers (Ed.), Applications of evolutionary computing. Lecture notes in computer science (Vol. 2037, pp. 70–79). Berlin: Springer.

    Google Scholar 

  • Doerner, K. F., Hartl, R. F., & Reimann, M. (2003). Competants for problem solving - the case of full truckload transportation. Central European Journal of Operations Research, 11(2), 115–141.

    Google Scholar 

  • Dorigo, M., & Gambardella, L. M. (1997). Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation, 1(1), 53–66.

    Article  Google Scholar 

  • Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics - Part B, 26(1), 29–41.

    Article  Google Scholar 

  • Dorigo, M., & Stützle, T. (2010). Ant colony optimization: Overview and recent advances. In M. Gendreau & J. Y. Potvin (Eds.), Handbook of metaheuristics. International series in operations research & management science (Vol. 146, pp. 227–263). New York: Springer US.

    Google Scholar 

  • Eilon, S., Watson-Gandy, C. D. T., & Christofides, N. (1971). Distribution management: mathematical modelling and practical analysis. London: Griffin.

    Google Scholar 

  • Feillet, D., & Dejax, P., & Gendreau, M. (2005). Traveling salesman problems with profits. Transportation Science, 39(2), 188–205.

    Google Scholar 

  • Fisher, M. L. (1994). Optimal solution of vehicle routing problems using minimum k-trees. Operations Research, 42(4), 626–642.

    Article  Google Scholar 

  • Fuellerer, G., Doerner, K. F., Hartl, R. F., & Iori, M. (2009). Ant colony optimization for the two-dimensional loading vehicle routing problem. Computers & Operations Research, 36(3), 655–673.

    Article  Google Scholar 

  • Fuellerer, G., Doerner, K. F., Hartl, R. F., & Iori, M. (2010) Metaheuristics for vehicle routing problems with three-dimensional loading constraints. European Journal of Operational Research, 201(3), 751–759.

    Article  Google Scholar 

  • Gansterer, M., Kücüktepe, M., & Hartl, R. F. (2015). The multi vehicle profitable pickup and delivery problem. Manuscript submitted for publication.

    Google Scholar 

  • Gélinas, S., Desrochers, M., Desrosiers, J., & Solomon, M. M. (1995). A new branching strategy for time constrained routing problems with application to backhauling. Annals of Operations Research, 61(1), 91–109.

    Article  Google Scholar 

  • Gendreau, M., Iori, M., Laporte, G., & Martello, S. (2006). A tabu search algorithm for a routing and container loading problem. Transportation Science, 40(3), 342–350.

    Article  Google Scholar 

  • Gendreau, M., Laporte, G., & Semet, F. (1997). The covering tour problem. Operations Research, 45(4), 568–576.

    Article  Google Scholar 

  • Gendreau, M., & Potvin, J. Y. (2010). Tabu search. In M. Gendreau & J. Y. Potvin (Eds.), Handbook of metaheuristics. International series in operations research & management science (Vol. 146, pp. 41–59). New York: Springer US.

    Google Scholar 

  • Glover, F. (1986). Future paths for integer programming and links to artificial intelligence. Computers & Operations Research, 13(5), 533–549. Applications of Integer Programming.

    Google Scholar 

  • Glover, F., & Laguna, M. (1997). Tabu search. Norwell, MA: Kluwer Academic Publishers.

    Book  Google Scholar 

  • Golden, B. L., Raghavan, R., & Wasil, E. A. (Eds.). (2008). The vehicle routing problem: Latest advances and new challenges. New York: Springer.

    Google Scholar 

  • Golden, B. L., Wasil, E. A., Kelly, J. P., & Chao, I. M. (1998). The impact of metaheuristics on solving the vehicle routing problem: Algorithms, problem sets, and computational results. In Fleet management and logistics (pp. 33–56). New York: Springer US.

    Chapter  Google Scholar 

  • Golden, B. L., & Wong, R. T. (1981). Capacitated arc routing problems. Networks, 11(3), 305–315.

    Google Scholar 

  • Gronalt, M., Hartl, R. F., & Reimann, M. (2003). New savings based algorithms for time constrained pickup and delivery of full truckloads. European Journal of Operational Research, 151(3), 520–535.

    Google Scholar 

  • Groër, C., Golden, B. L., & Wasil, E. A. (2009). The consistent vehicle routing problem. Manufacturing & Service Operations Management, 11(4), 630–643.

    Article  Google Scholar 

  • Gussmagg-Pfliegl, E., Tricoire, F., Doerner, K. F., Hartl, R. F., & Irnich, S. (2011). Heuristics for a real-world mail delivery problem. In C. Di Chio, A. Brabazon, G. Di Caro, R. Drechsler, M. Farooq, J. Grahl, G. Greenfield, C. Prins, J. Romero, G. Squillero, E. Tarantino, A. Tettamanzi, N. Urquhart, & A. Uyar (Eds.), Applications of evolutionary computation. Lecture notes in computer science (Vol. 6625, pp. 481–490). Berlin: Springer.

    Google Scholar 

  • Gutjahr, W. J., Katzensteiner, S., & Reiter, P. (2007). A VNS algorithm for noisy problems and its application to project portfolio analysis. In J. Hromkovič R. Královič, M. Nunkesser, & P. Widmayer (Eds.), Stochastic algorithms: Foundations and applications. Lecture notes in computer science (Vol. 4665, pp. 93–104). Berlin: Springer.

    Google Scholar 

  • Hansen, P., Mladenović, N., Brimberg, J., & Pérez, J. A. M. (2010). Variable neighborhood search. In M. Gendreau & J. Y. Potvin (Eds.), Handbook of Metaheuristics, International series in operations research & management science (Vol. 146, pp. 61–86). New York: Springer US.

    Google Scholar 

  • Hartl, R. F., & Romauch, M. (2013). The influence of routing on lateral transhipment. In R. Moreno-Díaz, F. Pichler, & A. Quesada-Arencibia (Eds.), Computer aided systems theory - EUROCAST 2013. Lecture notes in computer science (Vol. 8111, pp. 267–275). Berlin: Springer.

    Google Scholar 

  • Hartl, R. F., & Romauch, M. (2016). Notes on the single route lateral transhipment problem. Journal of Global Optimization, 65(1), 57–82.

    Article  Google Scholar 

  • Hemmelmayr, V. C., Doerner, K. F., & Hartl, R. F. (2009a). A variable neighborhood search heuristic for periodic routing problems. European Journal of Operational Research, 195(3), 791–802.

    Article  Google Scholar 

  • Hemmelmayr, V. C., Doerner, K. F., Hartl, R. F., & Rath, S. (2013). A heuristic solution method for node routing based solid waste collection problems. Journal of Heuristics 19(2), 129–156.

    Article  Google Scholar 

  • Hemmelmayr, V. C., Doerner, K. F., Hartl, R. F., & Savelsbergh, M. W. P. (2009b). Delivery strategies for blood products supplies. OR Spectrum, 31(4), 707–725.

    Article  Google Scholar 

  • Hemmelmayr, V. C., Doerner, K. F., Hartl, R. F., & Savelsbergh, M. W. P. (2010). Vendor managed inventory for environments with stochastic product usage. European Journal of Operational Research, 202(3), 686–695.

    Article  Google Scholar 

  • Hemmelmayr, V. C., Doerner, K. F., Hartl, R. F., & Vigo, D. (2014). Models and algorithms for the integrated planning of bin allocation and vehicle routing in solid waste management. Transportation Science, 48(1), 103–120.

    Article  Google Scholar 

  • Hiermann, G., Puchinger, J., Ropke, S., & Hartl, R. F. (2016). The electric fleet size and mix vehicle routing problem with time windows and recharging stations. European Journal of Operational Research, 252(3), 995–1018.

    Article  Google Scholar 

  • Ichoua, S., & Gendreau, M., & Potvin, J. -Y. (2003). Vehicle dispatching with time-dependent travel times. European Journal of Operational Research, 144(2), 379–396.

    Google Scholar 

  • Iori, M. (2004). Metaheuristic algorithms for combinatorial optimization problems. Ph.D. thesis, University of Bologna.

    Google Scholar 

  • Jacobs-Blecha, C. D., & Goetschalckx, M. (1992). The vehicle routing problem with backhauls: Properties and solution algorithms. Material Handling Research Center, Georgia Institute of Technology.

    Google Scholar 

  • Jozefowiez, N., Semet, F., & Talbi, E. G. (2002). Parallel and hybrid models for multi-objective optimization: Application to the vehicle routing problem. In J. Guervós, P. Adamidis, H. G. Beyer, H. P. Schwefel, & J. L. Fernández-Villacañas (Eds.), Parallel problem solving from nature - PPSN VII. Lecture notes in computer science (Vol. 2439, pp. 271–280). Berlin: Springer.

    Google Scholar 

  • Karp, R. M. (1972) Reducibility among combinatorial problems. In R. E. Miller & J. W. Thatcher (Eds.), Complexity of computer computations. The IBM research symposia series (pp. 85–103). New York: Plenum Press.

    Google Scholar 

  • Kiechle, G., Doerner, K. F, Gendreau, M., & Hartl, R. F. (2009). Waiting strategies for regular and emergency patient transportation. In B. Fleischmann, K. H. Borgwardt R. Klein, & A. Tuma (Eds.), Operations research proceedings 2008 (pp. 271–276). Berlin: Springer

    Chapter  Google Scholar 

  • Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680.

    Article  Google Scholar 

  • Knight, K. W., & Hofer, J. P. (1968). Vehicle scheduling with timed and connected calls: A case study. OR, 19(3), 299–310.

    Article  Google Scholar 

  • Kovacs, A. A., Golden, B. L., Hartl, R. F., & Parragh, S. N. (2015). The generalized consistent vehicle routing problem. Transportation Science, 49(4), 796–816.

    Article  Google Scholar 

  • Kovacs, A. A., Golden, B. L., Hartl, R. F., & Parragh, S. N. (2014b) Vehicle routing problems in which consistency considerations are important: A survey. Networks, 64(3), 192–213.

    Google Scholar 

  • Kovacs, A. A., Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2012). Adaptive large neighborhood search for service technician routing and scheduling problems. Journal of Scheduling, 15(5), 579–600.

    Article  Google Scholar 

  • Kovacs, A. A., Parragh, S. N., & Hartl, R. F. (2014c). A template-based adaptive large neighborhood search for the consistent vehicle routing problem. Networks, 63(1), 60–81.

    Article  Google Scholar 

  • Kovacs, A. A., Parragh, S. N., & Hartl, R. F. (2015). The multi-objective generalized consistent vehicle routing problem. European Journal of Operational Research, 247(2), 441–458.

    Article  Google Scholar 

  • Kritzinger, S., Tricoire, F., Doerner, K. F., & Hartl, R. F. (2011). Variable neighborhood search for the time-dependent vehicle routing problem with soft time windows. In C. Coello (Ed.), Learning and intelligent optimization. Lecture notes in computer science (Vol. 6683, pp. 61–75). Berlin: Springer.

    Google Scholar 

  • Kritzinger, S., Doerner, K. F., Hartl, R. F., Kiechle, G., Stadler, H., & Manohar, S. S. (2012). Using traffic information for time-dependent vehicle routing. Procedia - Social and Behavioral Sciences, 39, 217–229.

    Article  Google Scholar 

  • Kritzinger, S., Doerner, K. F., Tricoire, F., & Hartl, R. F. (2015a). Adaptive search techniques for problems in vehicle routing, Part I: A survey. Yugoslav Journal of Operations Research, 25(1), 3–31.

    Article  Google Scholar 

  • Kritzinger, S., Doerner, K. F., Tricoire, F., & Hartl, R. F. (2015b). Adaptive search techniques for problems in vehicle routing, Part II: A numerical comparison. Yugoslav Journal of Operations Research, 25(2), 169–184.

    Article  Google Scholar 

  • Kritzinger, S., Tricoire, F., Doerner, K. F., Hartl, R. F., & Stützle, T. (2014). A unified framework for routing problems with a fixed fleet size. Manuscript submitted for publication.

    Google Scholar 

  • Laporte, G. (2009). Fifty years of vehicle routing. Transportation Science, 43(4), 408–416.

    Article  Google Scholar 

  • Li, F., Golden, B. L., & Wasil, E. A. (2007). The open vehicle routing problem: Algorithms, large-scale test problems, and computational results. Computers and Operations Research, 34(10), 2918–2930.

    Article  Google Scholar 

  • Liu, F. H., & Shen, S. Y. (1999). The fleet size and mix vehicle routing problem with time windows. The Journal of the Operational Research Society, 50(7), 721–732.

    Article  Google Scholar 

  • Lokin, F. C. J. (1979). Procedures for travelling salesman problems with additional constraints. European Journal of Operational Research, 3(2), 135–141.

    Article  Google Scholar 

  • Mladenović, N., & Hansen, P. (1997). Variable neighborhood search. Computers & Operations Research, 24(11), 1097–1100.

    Article  Google Scholar 

  • Moscato, P., & Cotta, C. (2010). A modern introduction to memetic algorithms. In M Gendreau, J. Y. Potvin (Eds.), Handbook of metaheuristics. International series in operations research & management science (Vol. 146, pp. 141–183). New York: Springer US.

    Google Scholar 

  • Mu, Q., Fu, Z., Lysgaard, J., & Eglese, R. W. (2011). Disruption management of the vehicle routing problem with vehicle breakdown. Journal of the Operational Research Society, 62(4), 742–749.

    Article  Google Scholar 

  • Nikolaev, A. G., & Jacobson, S. H. (2010). Simulated annealing. In M. Gendreau & J. Y. Potvin (Eds.), Handbook of metaheuristics. International series in operations research & management science (Vol. 146, pp. 1–39). New York: Springer US.

    Google Scholar 

  • Nolz, P. C., Doerner, K. F., Gutjahr, W. J., & Hartl, R. F. (2010a). A bi-objective metaheuristic for disaster relief operation planning. In C. Coello Coello, C. Dhaenens, & L. Jourdan (Eds.), Advances in multi-objective nature inspired computing. Studies in computational intelligence (Vol. 272, pp. 167–187). Berlin: Springer.

    Google Scholar 

  • Nolz, P. C., Doerner, K. F., & Hartl, R. F. (2010b). Water distribution in disaster relief. International Journal of Physical Distribution & Logistics Management, 40(8/9), 693–708.

    Article  Google Scholar 

  • Nolz, P. C., Semet, F., & Doerner, K. F. (2011). Risk approaches for delivering disaster relief supplies. OR Spectrum, 33(3), 543–569.

    Article  Google Scholar 

  • Ostertag, A., Doerner, K. F., & Hartl, R. F. (2008). A variable neighborhood search integrated in the popmusic framework for solving large scale vehicle routing problems. In M. Blesa, C. Blum, C. Cotta, A. Fernández, J. Gallardo, A. Roli, & M. Sampels (Eds.), Hybrid metaheuristics. Lecture notes in computer science. (Vol. 5296, pp. 29–42) Berlin: Springer.

    Google Scholar 

  • Ostertag, A., Doerner, K. F., Hartl, R. F., Taillard, É. D., & Waelti, P. (2009) Popmusic for a real-world large-scale vehicle routing problem with time windows. Journal of The Operational Research Society, 60(7), 934–943.

    Article  Google Scholar 

  • Parragh, S. N. (2009). Ambulance routing problems with rich constraints and multiple objectives. Ph.D. thesis, University of Vienna.

    Google Scholar 

  • Parragh, S. N. (2011). Introducing heterogeneous users and vehicles into models and algorithms for the dial-a-ride problem. Transportation Research Part C: Emerging Technologies 19(5), 912–930.

    Article  Google Scholar 

  • Parragh, S. N., Cordeau, J. F., Doerner, K. F., & Hartl, R. F. (2012). Models and algorithms for the heterogeneous dial-a-ride problem with driver-related constraints. OR Spectrum, 34(3), 593–633.

    Article  Google Scholar 

  • Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008a). A survey on pickup and delivery problems. Part I: Transportation between customers and depot. Journal für Betriebswirtschaft, 58(1), 21–51.

    Article  Google Scholar 

  • Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008b). A survey on pickup and delivery problems. Part II: Transportation between pickup and delivery locations. Journal für Betriebswirtschaft, 58(2), 81–117.

    Article  Google Scholar 

  • Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2010a). Demand responsive transportation. In J. J. Cochran, L. A. Cox, P. Keskinocak, J. P. Kharoufeh, & J. C. Smith (Eds.), Wiley encyclopedia of operations research and management science. New York: Wiley.

    Google Scholar 

  • Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2010b). Variable neighborhood search for the dial-a-ride problem. Computers & Operations Research, 37(6), 1129–1138.

    Article  Google Scholar 

  • Parragh, S. N., Doerner, K. F., Hartl, R. F., & Gandibleux, X. (2009). A heuristic two-phase solution approach for the multi-objective dial-a-ride problem. Networks, 54, 227–242.

    Article  Google Scholar 

  • Parragh, S. N., & Schmid, V. (2013). Hybrid column generation and large neighborhood search for the dial-a-ride problem. Computers & Operations Research, 40(1), 490–497.

    Article  Google Scholar 

  • Pasia, J. M., Doerner, K. F., Hartl, R. F., & Reimann, M. (2007). A population-based local search for solving a bi-objective vehicle routing problem. In C. Cotta & J van Hemert (Eds.), Evolutionary computation in combinatorial optimization. Lecture notes in computer science. (Vol. 4446, pp. 166–175). Berlin: Springer.

    Google Scholar 

  • Pisinger, D., & Ropke, S. (2010). Large neighborhood search. In M. Gendreau & J. Y. Potvin (Eds.), Handbook of metaheuristics. International series in operations research & management science (Vol. 146, pp. 399–419). New York: Springer US.

    Google Scholar 

  • Polacek, M., Benkner, S., Doerner, K. F., & Hartl, R. F. (2008a). A cooperative and adaptive variable neighborhood search for the multi depot vehicle routing problem with time windows. BuR - Business Research, 1(2), 207–218.

    Article  Google Scholar 

  • Polacek, M., Doerner, K. F., Hartl, R. F., Kiechle, G., & Reimann, M. (2007). Scheduling periodic customer visits for a traveling salesperson. European Journal of Operational Research, 179(3), 823–837.

    Article  Google Scholar 

  • Polacek, M., Doerner, K. F., Hartl, R. F., & Maniezzo, V. (2008b). A variable neighborhood search for the capacitated arc routing problem with intermediate facilities. Journal of Heuristics, 14(5), 405–423.

    Article  Google Scholar 

  • Polacek, M., Hartl, R. F., Doerner, K. F., & Reimann, M. (2004). A variable neighborhood search for the multi depot vehicle routing problem with time windows. Journal of Heuristics, 10(6), 613–627.

    Article  Google Scholar 

  • Pullen, H. G. M., & Webb, M. H. J. (1967). A computer application to a transport scheduling problem. The Computer Journal, 10(1), 10–13.

    Article  Google Scholar 

  • Reimann, M., Doerner, K. F., & Hartl, R. F. (2002a). Insertion based ants for vehicle routing problems with backhauls and time windows. In M. Dorigo, G. Di Caro, & M. Sampels (Eds.), Ant algorithms. Lecture notes in computer science. (Vol. 2463, pp. 135–148). Berlin: Springer.

    Google Scholar 

  • Reimann, M., Doerner, K. F., & Hartl, R. F. (2003). Analyzing a unified ant system for the VRP and some of its variants. In G. Raidl, S. Cagnoni, J. J. R. Cardalda, D. W. Corne, J. Gottlieb, & A. Guillot (Eds.), Applications of evolutionary computing. Lecture notes in computer science (Vol. 2611, pp. 300–310). Berlin: Springer.

    Google Scholar 

  • Reimann, M., Doerner, K. F., & Hartl, R. F. (2004). D-Ants: Savings based ants divide and conquer the vehicle routing problem. Computers & Operations Research, 31(4), 563–591.

    Article  Google Scholar 

  • Reimann, M., Stummer, M., & Doerner, K. F. (2002b). A savings based ant system for the vehicle routing problem. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO ’02 (pp. 1317–1326). San Francisco, CA: Morgan Kaufmann Publishers Inc.

    Google Scholar 

  • Reimann, M., & Ulrich, H. (2006). Comparing backhauling strategies in vehicle routing using ant colony optimization. Central European Journal of Operations Research, 14(2), 105–123.

    Article  Google Scholar 

  • Resende, M. G. C., Ribeiro, C. C., Glover, F., & Martí, R. (2010). Scatter search and path-relinking: Fundamentals, advances, and applications. In M. Gendreau & J. Y. Potvin (Eds.), Handbook of metaheuristics. International series in operations research & management science (Vol. 146, pp. 87–107). New York: Springer US.

    Google Scholar 

  • Ritzinger, U., Puchinger, J., & Hartl, R. F. (2014). Dynamic programming based metaheuristics for the dial-a-ride problem. Annals of Operations Research, 236(2), 341–358.

    Article  Google Scholar 

  • Ritzinger, U., Puchinger, J., & Hartl, R. F. (2016). A survey on dynamic and stochastic vehicle routing problems. International Journal of Production Research, 54(1), 215–231.

    Article  Google Scholar 

  • Ropke, S., & Pisinger, D. (2006). An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transportation Science, 40(4), 455–472.

    Article  Google Scholar 

  • Russell, R., & Igo, W. (1979). An assignment routing problem. Networks, 9(1), 1–17.

    Article  Google Scholar 

  • Russell, R. A., & Gribbin, D. (1991). A multiphase approach to the period routing problem. Networks, 21(7), 747–765.

    Article  Google Scholar 

  • Schilde, M., Doerner, K. F., & Hartl, R. F. (2011). Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports. Computers & Operations Research, 38(12), 1719–1730.

    Article  Google Scholar 

  • Schilde, M., Doerner, K. F., & Hartl, R. F. (2014). Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem. European Journal of Operational Research, 238(1), 18–30.

    Article  Google Scholar 

  • Schilde, M., Doerner, K. F., Hartl, R. F., & Kiechle, G. (2009). Metaheuristics for the bi-objective orienteering problem. Swarm Intelligence, 3(3), 179–201.

    Article  Google Scholar 

  • Schmid, V., Doerner, K. F., Hartl, R. F., & Salazar-González, J. J. (2010) Hybridization of very large neighborhood search for ready-mixed concrete delivery problems. Computers & Operations Research, 37(3), 559–574.

    Article  Google Scholar 

  • Schmid, V., Doerner, K. F., Hartl, R. F., Savelsbergh, M. W. P., & Stoecher, W. (2009). A hybrid solution approach for ready-mixed concrete delivery. Transportation Science, 43(1), 70–85.

    Article  Google Scholar 

  • Schneider, M., Stenger, A., & Goeke, D. (2014). The electric vehicle-routing problem with time windows and recharging stations. Transportation Science, 48(4), 500–520.

    Article  Google Scholar 

  • Shaw, P. (1998). Using constraint programming and local search methods to solve vehicle routing problems. In M. Maher & J. F. Puget (Eds.), Principles and practice of constraint programming - CP98. Lecture notes in computer science (Vol. 1520, pp. 417–431). Berlin: Springer.

    Google Scholar 

  • Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35(2), 254–265.

    Article  Google Scholar 

  • Steadie, S. M., Dellaert, N. P., Nuijten, W., Van Woensel, T., & Raoufi, R. (2014). Multimodal freight transportation planning: A literature review. European Journal of Operational Research 233(1), 1–15.

    Article  Google Scholar 

  • Strodl, J., Doerner, K. F., Tricoire, F., & Hartl, R. F. (2010). On index structures in hybrid metaheuristics for routing problems with hard feasibility checks: An application to the 2-dimensional loading vehicle routing problem. In M. Blesa, C. Blum, G. Raidl, A. Roli, & M. Sampels (Eds.), Hybrid metaheuristics. Lecture notes in computer science (Vol. 6373, pp. 160–173). Berlin: Springer.

    Google Scholar 

  • Toth, P., & Vigo, D. (2001a). An overview of vehicle routing problems. In P. Toth & D. Vigo (Eds.), The vehicle routing problem (pp. 1–26). Philadelphia: Society for Industrial and Applied Mathematics.

    Google Scholar 

  • Toth, P., & Vigo, D. (Eds.). (2001b). The vehicle routing problem. Philadelphia: Society for Industrial and Applied Mathematics.

    Google Scholar 

  • Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing. Philadelphia: Society for Industrial and Applied Mathematics.

    Google Scholar 

  • Tricoire, F. (2012). Multi-directional local search. Computers & Operations Research, 39(12), 3089–3101.

    Article  Google Scholar 

  • Tricoire, F., Doerner, K. F., Hartl, R. F., & Iori, M. (2011). Heuristic and exact algorithms for the multi-pile vehicle routing problem. OR Spectrum, 33(4), 931–959.

    Article  Google Scholar 

  • Tricoire, F., Romauch, M., Doerner, K. F., & Hartl, R. F. (2010). Heuristics for the multi-period orienteering problem with multiple time windows. Computers & Operations Research, 37(2), 351–367.

    Article  Google Scholar 

  • Tricoire, F., Romauch, M., Doerner, K. F., & Hartl, R. F. (2013). Addendum: Addendum to “heuristics for the multi-period orienteering problem with multiple time windows”. Computers & Operations Research, 40(5), 1516–1519.

    Article  Google Scholar 

  • Tsiligirides, T. (1984). Heuristic methods applied to orienteering. The Journal of the Operational Research Society, 35(9), 797–809.

    Article  Google Scholar 

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Acknowledgements

The financial support by the Austrian Federal Ministry of Science, Research and Economy and the National Foundation for Research, Technology and Development is gratefully acknowledged.

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Doerner, K.F., Kiefer, A., Wolfinger, D. (2016). Twenty Years of Vehicle Routing in Vienna. In: Dawid, H., Doerner, K., Feichtinger, G., Kort, P., Seidl, A. (eds) Dynamic Perspectives on Managerial Decision Making. Dynamic Modeling and Econometrics in Economics and Finance, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-39120-5_26

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