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The Multi-Objective Shortest Path Problem with Multimodal Transportation for Emergency Logistics

Author

Listed:
  • Jinzuo Guo

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
    These authors contributed equally to this work.)

  • Hongbin Liu

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
    These authors contributed equally to this work.)

  • Tianyu Liu

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Guopeng Song

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Bo Guo

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

Abstract

The optimization of emergency logistical transportation is crucial for the timely dispatch of aid and support to affected areas. By incorporating practical constraints into emergency logistics, this study establishes a multi-objective shortest path mixed-integer programming model based on a multimodal transportation network. To solve multi-objective shortest path problems with multimodal transportation, we design an ideal point method and propose a procedure for constructing the complete Pareto frontier based on the k -shortest path multi-objective algorithm. We use modified Dijkstra and Floyd multimodal transportation shortest path algorithms to build a k -shortest path multi-objective algorithm. The effectiveness of the proposed multimodal transportation shortest path algorithm is verified using empirical experiments carried out on test sets of different scales and a comparison of the runtime using a commercial solver. The results show that the modified Dijkstra algorithm has a runtime that is 100 times faster on average than the modified Floyd algorithm, which highlights its greater applicability in large-scale multimodal transportation networks, demonstrating that the proposed method both has practical significance and can generate satisfactory solutions to the multi-objective shortest path problem with multimodal transportation in the context of emergency logistics.

Suggested Citation

  • Jinzuo Guo & Hongbin Liu & Tianyu Liu & Guopeng Song & Bo Guo, 2024. "The Multi-Objective Shortest Path Problem with Multimodal Transportation for Emergency Logistics," Mathematics, MDPI, vol. 12(17), pages 1-21, August.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:17:p:2615-:d:1462879
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    References listed on IDEAS

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    2. Yi, Wei & Kumar, Arun, 2007. "Ant colony optimization for disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 660-672, November.
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