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Multi-stage humanitarian emergency logistics: robust decisions in uncertain environment

Author

Listed:
  • Jianhui Du

    (Sichuan University)

  • Peng Wu

    (Sichuan University)

  • Yiqing Wang

    (Sichuan University)

  • Dan Yang

    (University of Glasgow)

Abstract

Humanitarian emergency logistics plays a vital role in mitigating the hazards of natural disasters. Previous studies have majorly focused on primary disasters, while ignoring secondary disasters. Hence, we developed a multi-stage mixed-integer linear programming model to investigate joint primary and secondary management strategies for enhancing service coverage and customer satisfaction. Unfortunately, the lack of informational assurance presented serious challenges. To withstand the effects of uncertainty, we converted the proposed model into a multi-stage robust model. We extended the scenario generation method based on actual case scenarios to ensure the compatibility of the research and optimized the algorithm using commercial solvers to boost computational efficiency. The results indicated that the multi-stage robust model may produce feasible logistics solutions even under the worst-case scenario. Uncertainty fluctuations might result in increased costs, but increasing safety parameters can enhance overall service levels.

Suggested Citation

  • Jianhui Du & Peng Wu & Yiqing Wang & Dan Yang, 2023. "Multi-stage humanitarian emergency logistics: robust decisions in uncertain environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(1), pages 899-922, January.
    • Handle: RePEc:spr:nathaz:v:115:y:2023:i:1:d:10.1007_s11069-022-05578-3
    DOI: 10.1007/s11069-022-05578-3
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    References listed on IDEAS

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    Cited by:

    1. Fang Xu & Yifan Ma & Chang Liu & Ying Ji, 2024. "Emergency Logistics Facilities Location Dual-Objective Modeling in Uncertain Environments," Sustainability, MDPI, vol. 16(4), pages 1-34, February.

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