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A Collaborative Distribution Mode Based on Unmanned Vehicle-Traction Cabinet in Emergency

Author

Listed:
  • Jiaxin Li

    (Beijing University of Posts and Telecommunications)

  • Mengke Yang

    (Beijing University of Posts and Telecommunications)

  • Yating Li

    (Beijing University of Posts and Telecommunications)

  • Fengyang Hu

    (Beijing University of Posts and Telecommunications)

  • Tao Wang

    (Beijing University of Posts and Telecommunications)

  • Baoshun Tian

    (Beijing University of Posts and Telecommunications)

Abstract

In recent years, the application of unmanned vehicles for efficient emergency distribution has become more important in public health events, and the existing distribution methods are difficult to satisfy the needs of customers with different degrees of urgency due to limited capacity. The paper proposes a collaborative distribution mode based on unmanned vehicles and traction cabinets to solve these problems. Firstly, introducing the traction cabinet to the background of public health events, the paper proposes an emergency distribution mode of unmanned vehicle collaborative traction cabinet classified according to customer emergency degree. Secondly, the paper proposes a two-stage model combining the drop-off network location problem and routing problem, solved by an improved NSGA-II algorithm and a genetic simulated annealing algorithm. Finally, based on the relevant real data of Chaoyang District, Beijing, China, the paper designs simulation experiments. The distribution scheme solved in this paper is compared with the ordinary scheme from the aspects of path length, vehicles, and violation of constraints. It can be concluded that the model designed in the paper can better satisfy the needs of emergency distribution and achieve efficient hierarchical distribution.

Suggested Citation

  • Jiaxin Li & Mengke Yang & Yating Li & Fengyang Hu & Tao Wang & Baoshun Tian, 2025. "A Collaborative Distribution Mode Based on Unmanned Vehicle-Traction Cabinet in Emergency," Lecture Notes in Operations Research,, Springer.
  • Handle: RePEc:spr:lnopch:978-981-96-9697-0_30
    DOI: 10.1007/978-981-96-9697-0_30
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