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A Bucket Graph–Based Labeling Algorithm with Application to Vehicle Routing

Author

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  • Ruslan Sadykov

    (INRIA Bordeaux Sud-Ouest, 33405 Talence, France; Institute of Mathematics, University of Bordeaux, 3340 Talence, France;)

  • Eduardo Uchoa

    (Engenharia de Produção, Universidade Federal Fluminense, Niterói, Brasil, 24210-240)

  • Artur Pessoa

    (Engenharia de Produção, Universidade Federal Fluminense, Niterói, Brasil, 24210-240)

Abstract

We consider the shortest path problem with resource constraints arising as a subproblem in state-of-the-art branch-cut-and-price algorithms for vehicle routing problems. We propose a variant of the bidirectional label-correcting algorithm in which the labels are stored and extended according to the so-called bucket graph. This organization of labels helps to significantly decrease the number of dominance checks and the running time of the algorithm. We also show how the forward/backward route symmetry can be exploited and how to eliminate arcs from the bucket graph using reduced costs. The proposed algorithm can be especially beneficial for vehicle routing instances with large vehicle capacity and/or with time window constraints. Computational experiments were performed on instances from the distance-constrained vehicle routing problem, including multidepot and site-dependent variants, on the vehicle routing problem with time windows, and on the “nightmare” instances of the heterogeneous fleet vehicle routing problem. Significant improvements over the best algorithms in the literature were achieved, and many instances could be solved for the first time.

Suggested Citation

  • Ruslan Sadykov & Eduardo Uchoa & Artur Pessoa, 2021. "A Bucket Graph–Based Labeling Algorithm with Application to Vehicle Routing," Transportation Science, INFORMS, vol. 55(1), pages 4-28, 1-2.
  • Handle: RePEc:inm:ortrsc:v:55:y:2021:i:1:p:4-28
    DOI: 10.1287/trsc.2020.0985
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    References listed on IDEAS

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    Cited by:

    1. Bock, Stefan, 2024. "Vehicle routing for connected service areas - a versatile approach covering single, hierarchical, and bi-criteria objectives," European Journal of Operational Research, Elsevier, vol. 313(3), pages 905-925.
    2. Liu, Yiming & Roberto, Baldacci & Zhou, Jianwen & Yu, Yang & Zhang, Yu & Sun, Wei, 2023. "Efficient feasibility checks and an adaptive large neighborhood search algorithm for the time-dependent green vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 310(1), pages 133-155.
    3. Schmidt, Carise E. & Silva, Arinei C.L. & Darvish, Maryam & Coelho, Leandro C., 2023. "Time-dependent fleet size and mix multi-depot vehicle routing problem," International Journal of Production Economics, Elsevier, vol. 255(C).
    4. Stefan Faldum & Timo Gschwind & Stefan Irnich, 2023. "Subset-Row Inequalities and Unreachability in Path-based Formulations for Routing and Scheduling Problems," Working Papers 2310, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    5. Feng Li & Wenjing Ai & Tianli Ju, 2022. "Cold Chain Logistics Distribution Path Planning of Fresh Products in Beijing Subcenter," Sustainability, MDPI, vol. 14(17), pages 1-25, August.
    6. Froger, Aurélien & Sadykov, Ruslan, 2023. "New exact and heuristic algorithms to solve the prize-collecting job sequencing problem with one common and multiple secondary resources," European Journal of Operational Research, Elsevier, vol. 306(1), pages 65-82.

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