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A metaheuristic for the vehicle-routeing problem with soft time windows

Author

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  • W-C Chiang

    (Operations Management, University of Tulsa)

  • R A Russell

    (Operations Management, University of Tulsa)

Abstract

This paper develops a metaheuristic for the vehicle-routeing and scheduling problem with soft time window constraints. A tabu search solution method is developed, which utilizes a mixed neighbourhood structure and an advanced recovery procedure to generate high-quality solutions. Computational results on test problems from the literature are reported. The metaheuristic achieves solutions that compare favourably with previously reported results.

Suggested Citation

  • W-C Chiang & R A Russell, 2004. "A metaheuristic for the vehicle-routeing problem with soft time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1298-1310, December.
  • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:12:d:10.1057_palgrave.jors.2601791
    DOI: 10.1057/palgrave.jors.2601791
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    References listed on IDEAS

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    1. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
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    5. Yiannis A. Koskosidis & Warren B. Powell & Marius M. Solomon, 1992. "An Optimization-Based Heuristic for Vehicle Routing and Scheduling with Soft Time Window Constraints," Transportation Science, INFORMS, vol. 26(2), pages 69-85, May.
    6. Wen-Chyuan Chiang & Robert A. Russell, 1997. "A Reactive Tabu Search Metaheuristic for the Vehicle Routing Problem with Time Windows," INFORMS Journal on Computing, INFORMS, vol. 9(4), pages 417-430, November.
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    Citations

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    Cited by:

    1. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    2. R A Russell & T L Urban, 2008. "Vehicle routing with soft time windows and Erlang travel times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1220-1228, September.
    3. Lei Chen & Haiyan Ma & Yi Wang & Feng Li, 2022. "Vehicle Routing Problem for the Simultaneous Pickup and Delivery of Lithium Batteries of Small Power Vehicles under Charging and Swapping Mode," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    4. Sébastien Mouthuy & Florence Massen & Yves Deville & Pascal Van Hentenryck, 2015. "A Multistage Very Large-Scale Neighborhood Search for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 49(2), pages 223-238, May.
    5. Andres Figliozzi, Miguel, 2012. "The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 616-636.
    6. Daniel Schubert & André Scholz & Gerhard Wäscher, 2017. "Integrated Order Picking and Vehicle Routing with Due Dates," FEMM Working Papers 170007, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    7. Matteo Salani & Maria Battarra, 2018. "The opportunity cost of time window violations," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(4), pages 343-361, December.
    8. Z Fu & R Eglese & L Y O Li, 2008. "A unified tabu search algorithm for vehicle routing problems with soft time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 663-673, May.
    9. Junlong Zhang & William Lam & Bi Chen, 2013. "A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service," Networks and Spatial Economics, Springer, vol. 13(4), pages 471-496, December.
    10. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    11. Jbili, S. & Chelbi, A. & Radhoui, M. & Kessentini, M., 2018. "Integrated strategy of Vehicle Routing and Maintenance," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 202-214.
    12. Md. Anisul Islam & Yuvraj Gajpal, 2021. "Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    13. Daniel Schubert & André Scholz & Gerhard Wäscher, 2018. "Integrated order picking and vehicle routing with due dates," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 1109-1139, October.
    14. Kuhn, Heinrich & Schubert, Daniel & Holzapfel, Andreas, 2021. "Integrated order batching and vehicle routing operations in grocery retail – A General Adaptive Large Neighborhood Search algorithm," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1003-1021.

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