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A variable neighborhood search algorithm for the location problem of platoon formation center

Author

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  • Zhaojie Xue

    (Shenzhen University
    Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education
    Underground Polis Academy, Shenzhen University)

  • Wenxiang Peng

    (Shenzhen University
    Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education
    Underground Polis Academy, Shenzhen University)

  • Haipeng Cui

    (Shenzhen University
    Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education
    Underground Polis Academy, Shenzhen University)

Abstract

Autonomous platooning technology has been considered a promising solution for reducing costs in the trucking industry. In trucking networks, the operation of autonomous truck platoons is constrained by many factors such as network topology, travel distance, and demand distribution, indicating the importance of deciding when and where to form and decompose platoons. This study investigates a novel location problem for platoon formation center (PFC) in a trucking network, which plays an important role in platooning operations. PFCs are specifically constructed as infrastructures for the formation and decomposition of truck platoons. Semi-automated truck platoons traveling between PFCs save labor and fuel. Therefore, each origin–destination (OD) pair in the trucking network can choose a beneficial transportation route via PFCs. This study aims to find the optimal PFC location scheme and OD demand routing scheme to minimize the total cost, which includes PFC construction, driver labor, and truck fuel costs. Accordingly, a mixed-integer linear programming model is developed. To effectively solve large-scale problems in practical applications, a variable neighborhood search algorithm embedded with a heuristic routing allocation algorithm is designed. We construct 20 instances with different characteristics, such as the number and distribution of customer nodes and PFC candidate nodes; construction cost of PFC candidate nodes; and amount and distribution of OD demand. We evaluate the efficiency of the algorithm based on the experimental results. Furthermore, the benefits of the new transportation mode are quantified, and planners are provided with insights into PFC construction.

Suggested Citation

  • Zhaojie Xue & Wenxiang Peng & Haipeng Cui, 2024. "A variable neighborhood search algorithm for the location problem of platoon formation center," Flexible Services and Manufacturing Journal, Springer, vol. 36(4), pages 1292-1323, December.
  • Handle: RePEc:spr:flsman:v:36:y:2024:i:4:d:10.1007_s10696-023-09527-5
    DOI: 10.1007/s10696-023-09527-5
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    References listed on IDEAS

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    1. 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).
    2. Pierre Hansen & Nenad Mladenović & Raca Todosijević & Saïd Hanafi, 2017. "Variable neighborhood search: basics and variants," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(3), pages 423-454, September.
    3. Alumur, Sibel & Kara, Bahar Y., 2008. "Network hub location problems: The state of the art," European Journal of Operational Research, Elsevier, vol. 190(1), pages 1-21, October.
    4. Bhoopalam, Anirudh Kishore & Agatz, Niels & Zuidwijk, Rob, 2018. "Planning of truck platoons: A literature review and directions for future research," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 212-228.
    5. You, Jintao & Miao, Lixin & Zhang, Canrong & Xue, Zhaojie, 2020. "A generic model for the local container drayage problem using the emerging truck platooning operation mode," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 181-209.
    6. Stefan Irnich & Guy Desaulniers, 2005. "Shortest Path Problems with Resource Constraints," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 33-65, Springer.
    7. 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.
    8. Boysen, Nils & Briskorn, Dirk & Schwerdfeger, Stefan, 2018. "The identical-path truck platooning problem," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 26-39.
    9. 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.
    10. S. Sivanandham & M. S. Gajanand, 2020. "Platooning for sustainable freight transportation: an adoptable practice in the near future?," Transport Reviews, Taylor & Francis Journals, vol. 40(5), pages 581-606, July.
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