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The container drayage problem for heterogeneous trucks with multiple loads: A revisit

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  • Chen, Rui
  • Chen, Shukai
  • Cui, Haipeng
  • Meng, Qiang

Abstract

In this study, we revisit the container drayage problem for heterogeneous trucks with multiple loads in view of its practical significance. We first propose a tailored mixed-integer linear programming (MILP) model explicitly to reflect the reality of container drayage operations. To solve medium-scale problems more effectively, two relaxed MILP models are built to provide a solution that is close to optimal with less computational time. These two relaxed models are proven to work as intended and provide optimal solutions under certain conditions. Moreover, an effective hybrid heuristic method incorporating the cheapest feasible insertion mechanism and the variable neighborhood search scheme is designed to solve large-scale problems. Extensive numerical experiments demonstrate the scalability of the heuristic method in real-world applications.

Suggested Citation

  • Chen, Rui & Chen, Shukai & Cui, Haipeng & Meng, Qiang, 2021. "The container drayage problem for heterogeneous trucks with multiple loads: A revisit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:transe:v:147:y:2021:i:c:s1366554521000193
    DOI: 10.1016/j.tre.2021.102241
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    Cited by:

    1. Cui, Haipeng & Chen, Shukai & Chen, Rui & Meng, Qiang, 2022. "A two-stage hybrid heuristic solution for the container drayage problem with trailer reposition," European Journal of Operational Research, Elsevier, vol. 299(2), pages 468-482.
    2. Chen, Shukai & Wang, Hua & Meng, Qiang, 2021. "Autonomous truck scheduling for container transshipment between two seaport terminals considering platooning and speed optimization," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 289-315.
    3. Jia, Shuai & Cui, Haipeng & Chen, Rui & Meng, Qiang, 2022. "Dynamic container drayage with uncertain request arrival times and service time windows," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 237-258.
    4. Lange, Ann-Kathrin & Nellen, Nicole & Jahn, Carlos, 2022. "Truck appointment systems: How can they be improved and what are their limits?," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 615-655, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    5. Chen, Rui & Meng, Qiang & Jia, Peng, 2022. "Container port drayage operations and management: Past and future," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    6. Bustos-Coral, Daniel & Costa, Alysson M., 2022. "Drayage routing with heterogeneous fleet, compatibility constraints, and truck load configurations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    7. Yan, Xiaoyuan & Xu, Min & Xie, Chi, 2023. "Local container drayage problem with improved truck platooning operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    8. Yujian Song & Yuting Zhang & Wanli Wang & Ming Xue, 2023. "A Branch and Price Algorithm for the Drop-and-Pickup Container Drayage Problem with Empty Container Constraints," Sustainability, MDPI, vol. 15(7), pages 1-28, March.
    9. Chen, Rui & Jia, Shuai & Meng, Qiang, 2023. "Dynamic container drayage booking and routing decision support approach for E-commerce platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).

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