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The Vehicle Routing Problem with Transhipment Facilities

Author

Listed:
  • Roberto Baldacci

    (Department of Electrical, Electronic, and Information Engineering, University of Bologna, 47521 Cesena, Italy)

  • Sandra Ulrich Ngueveu

    (LAAS–CNRS, Université de Toulouse, CNRS, INP, F-31400 Toulouse, France)

  • Roberto Wolfler Calvo

    (Laboratoire d’Informatique de Paris Nord, Université de Paris 13, 93430 Villetaneuse, France; and Sorbonne Paris Cité, CNRS (UMR 7030), 93430 Villetaneuse, France)

Abstract

This paper proposes an exact method for solving an optimization problem arising in several distribution networks where customers can be served directly, using vehicle routes from a central depot, or through transhipment facilities. The problem consists of optimizing the following inter-dependent decisions: selecting transhipment facilities, allocating customers to these facilities, and designing vehicle routes emanating from a central depot to minimize the total distribution cost. This problem is called the Vehicle Routing Problem with Transhipment Facilities ( vrptf ). The paper describes two integer-programming formulations for the vrptf , i.e., an edge-flow based formulation and a Set Partitioning (SP) based formulation. The LP-relaxation of the two formulations are further strengthened by the addition of different valid inequalities. We also describe two new route relaxations used by dual ascent heuristics to find near-optimal dual solutions of LP-relaxation of the SP model. The valid inequalities and the route relaxations are used in a branch-and-cut-and-price approach to solve the problem to optimality. The proposed method is tested on a large family of instances, including real-world examples. The computational results obtained indicate the effectiveness of the proposed method.

Suggested Citation

  • Roberto Baldacci & Sandra Ulrich Ngueveu & Roberto Wolfler Calvo, 2017. "The Vehicle Routing Problem with Transhipment Facilities," Transportation Science, INFORMS, vol. 51(2), pages 592-606, May.
    • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:2:p:592-606
    DOI: 10.1287/trsc.2016.0711
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    References listed on IDEAS

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    Cited by:

    1. Guo, Chaojie & Thompson, Russell G. & Foliente, Greg & Kong, Xiang T.R., 2021. "An auction-enabled collaborative routing mechanism for omnichannel on-demand logistics through transshipment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    2. Su, E. & Qin, Hu & Li, Jiliu & Pan, Kai, 2023. "An exact algorithm for the pickup and delivery problem with crowdsourced bids and transshipment," Transportation Research Part B: Methodological, Elsevier, vol. 177(C).
    3. Adamo, Tommaso & Gendreau, Michel & Ghiani, Gianpaolo & Guerriero, Emanuela, 2024. "A review of recent advances in time-dependent vehicle routing," European Journal of Operational Research, Elsevier, vol. 319(1), pages 1-15.
    4. Chen, Cheng & Demir, Emrah & Huang, Yuan, 2021. "An adaptive large neighborhood search heuristic for the vehicle routing problem with time windows and delivery robots," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1164-1180.

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