交通运输系统工程与信息

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (3): 335-345.DOI: 10.16097/j.cnki.1009-6744.2025.03.030

• 工程应用与案例分析 • 上一篇    下一篇

洪涝灾害下考虑受灾点差异的应急物资分配-配送优化

刘长石1a，万城1b，王凤*1a，刘光洪2，陈宝玺1b   

  1. 1. 湖南工商大学，a.工商管理学院，b.智能工程与智能制造学院，长沙410205；2.中南大学，化学化工学院，长沙410083
  • 收稿日期:2025-02-10 修回日期:2025-03-09 接受日期:2025-03-17 出版日期:2025-06-25 发布日期:2025-06-22
  • 作者简介:刘长石(1975—)，男，湖南邵阳人，教授，博士。
  • 基金资助:
    国家社会科学基金(23BGL011)。

Emergency Supply Allocation and Delivery Optimization Considering Differences in Affected Areas During Flood Disasters

LIU Changshi1a, WAN Cheng1b, WANG Feng*1a, LIU Guanghong2, CHEN Baoxi1b   

  1. 1a. School of Management, 1b. School of Intelligent Engineering and Intelligent Manufacturing, Hunan University of Technology and Business, Changsha 410205, China; 2. Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
  • Received:2025-02-10 Revised:2025-03-09 Accepted:2025-03-17 Online:2025-06-25 Published:2025-06-22
  • Supported by:
    National Philosophy and Social Sciences Foundation of China (23BGL011)。

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摘要： 洪灾具有突发性，应急部门在灾害初期存在应急物资缺乏的情况，同时，洪灾各受灾点的灾情与受灾群体具有差异性，对应急物资的需求量和需求紧迫度各不相同。为此，本文运用熵权法评估各受灾点的风险等级，以所有受灾点的痛苦感知总和最小为目标构建应急物资分配模型；在此基础上，以总配送时间最短和所有受灾点的痛苦感知成本之和最小为目标构建卡车与冲锋艇协同配送应急物资的路径规划模型，并根据两个模型的特性分别设计蚁群算法和改进非支配排序遗传算法求解。根据2024年湖南省平江县洪灾数据设定场景，求解受灾点差异情景下的应急物资分配-配送方案。与等比例分配策略相比，考虑受灾点差异的应急物资分配方法可使所有受灾点的痛苦感知总和降低72.24%，更具合理性；与多目标人工蜂群算法比较，改进非支配排序遗传算法按照受灾点风险等级规划应急物资配送路径，使总配送时间和总痛苦感知成本分别减少3.96%和21.78%，有效提升了洪灾救援效果。

关键词: 物流工程, 路径规划, 改进非支配排序遗传算法, 应急物资分配-配送

Abstract: Flood disaster is characterized by their sudden onset, and emergency response agencies often face a shortage of relief supplies in the early stages. The severity of the flood and the affected populations vary across different disaster sites, leading to diverse demands for relief materials and differing levels of urgency. Initially, the entropy weight method is employed to evaluate the risk levels of each disaster point. A relief allocation model is formulated to minimize the total suffering perception across all disaster points. A collaborative distribution routes planning model for trucks and speedboats is developed, with the dual goals of minimizing the total delivery time and reducing the sum of suffering perception costs at all disaster points. To solve these models, ant colony optimization and an improved non-dominated sorting genetic algorithm-II are designed, and tailored to the specific characteristics of each model. Based on the data of the flood in Pingjiang County, Hunan Province in 2024, the relief allocation distribution scheme was solved under the different disaster point scenarios. Compared with the equal-proportional allocation strategy, the allocation method considering the difference of disaster sites can reduce the total perceived pain of all disaster sites by 72.24%, which is more reasonable. Compared with the multi-objective artificial bee colony algorithm, the improved non dominated sorting genetic algorithm-II planned the distribution route of emergency materials according to the risk level of disaster points, resulting in an average reduction of 3.96% in total delivery time and 21.78% in overall perceived suffering cost, thereby effectively enhancing flood rescue effectiveness.

Key words: logistics engineering, routes planning, improved non-dominated sorting genetic algorithm-II, relief allocation-delivery

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