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Local container drayage problem with truck platooning mode

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  • Xue, Zhaojie
  • Lin, Hui
  • You, Jintao

Abstract

This study examines the local container drayage problem under a semi-autonomous platooning mode. The benefits of this mode include labor cost saving via the semi-autonomous truck fleet and fuel cost saving via air drag reduction. The problem of routing drivers and trucks according to the characteristics of platooning is mathematically modeled. The lower bound is analyzed through comparison with the traditional mode. A tabu search heuristic is developed to solve the problem. Numerical experiments are conducted to assess the performance of the algorithm, quantify the benefits of the platooning mode, and analyze the effects of some key model parameters.

Suggested Citation

  • Xue, Zhaojie & Lin, Hui & You, Jintao, 2021. "Local container drayage problem with truck platooning mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:transe:v:147:y:2021:i:c:s136655452030853x
    DOI: 10.1016/j.tre.2020.102211
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    References listed on IDEAS

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    12. Zhang, Ruiyou & Lu, Jye-Chyi & Wang, Dingwei, 2014. "Container drayage problem with flexible orders and its near real-time solution strategies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 235-251.
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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. You, Jintao & Wang, Yuan & Xue, Zhaojie, 2023. "An exact algorithm for the multi-trip container drayage problem with truck platooning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    3. Li, Haijian & Zhang, Junjie & Sun, Xiaoliang & Niu, Jun & Zhao, Xiaohua, 2022. "A survey of vehicle group behaviors simulation under a connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    4. 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).
    5. 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).
    6. 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).
    7. Chen, Shukai & Wang, Hua & Meng, Qiang, 2023. "Cost allocation of cooperative autonomous truck platooning: Efficiency and stability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 119-141.
    8. 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.
    9. Boshuai Zhao & Roel Leus, 2022. "An improved decomposition-based heuristic for truck platooning," Papers 2210.05562, arXiv.org, revised Feb 2023.
    10. 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).

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