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New assignment algorithms for the multi-depot vehicle routing problem

Author

Listed:
  • I D Giosa

    (Universidad de la República Oriental del Uruguay)

  • I L Tansini

    (Universidad de la República Oriental del Uruguay)

  • I O Viera

    (Universidad de la República Oriental del Uruguay)

Abstract

This paper considers the design and analysis of algorithms for the multi-depot vehicle routing problem with time windows (MDVRPTW). Given the intrinsic difficulty of this problem class, approximation methods of the type ‘cluster first, route second’ (two-step approaches) seem to offer the most promise for practical size problems. After describing six heuristics for the cluster part (assignment of customers to depots) an initial computational study of their performance is conducted. Finding, as expected, that the heuristics with the best results (in terms of the routing results) are those with the largest computational efforts.

Suggested Citation

  • I D Giosa & I L Tansini & I O Viera, 2002. "New assignment algorithms for the multi-depot vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 977-984, September.
    • Handle: RePEc:pal:jorsoc:v:53:y:2002:i:9:d:10.1057_palgrave.jors.2601426
    DOI: 10.1057/palgrave.jors.2601426
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    Citations

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    Cited by:

    1. Zhou Xu & Brian Rodrigues, 2015. "A 3/2-Approximation Algorithm for the Multiple TSP with a Fixed Number of Depots," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 636-645, November.
    2. C. Y. Lam, 2021. "Optimizing logistics routings in a network perspective of supply and demand nodes," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(1), pages 357-377, March.
    3. Bartosz Sawik, 2024. "Optimizing Last-Mile Delivery: A Multi-Criteria Approach with Automated Smart Lockers, Capillary Distribution and Crowdshipping," Logistics, MDPI, vol. 8(2), pages 1-29, May.
    4. Zhang, Ke & Lin, Xi & Li, Meng, 2023. "Graph attention reinforcement learning with flexible matching policies for multi-depot vehicle routing problems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    5. L Tansini & O Viera, 2006. "New measures of proximity for the assignment algorithms in the MDVRPTW," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(3), pages 241-249, March.
    6. Tu, Wei & Fang, Zhixiang & Li, Qingquan & Shaw, Shih-Lung & Chen, BiYu, 2014. "A bi-level Voronoi diagram-based metaheuristic for a large-scale multi-depot vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 84-97.
    7. T R P Ramos & R C Oliveira, 2011. "Delimitation of service areas in reverse logistics networks with multiple depots," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1198-1210, July.
    8. Xie, Lin & Li, Hanyi & Luttmann, Laurin, 2023. "Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses," European Journal of Operational Research, Elsevier, vol. 307(2), pages 713-730.

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