突发公共卫生事件下救援物资配送方案研究  

Investigation into relief materials distribution schemes during public health emergencies

作　　者：帅春燕 张婷 王文聪 欧阳鑫[3] SHUAI Chunyan;ZHANG Ting;WANG Wencong;OUYANG Xin(School of Transportation Engineering,Kunming University of Science and Technology,Kunming 650500,China;Hekou County Transportation Bureau,Honghe 661300,Yunnan,China;School of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学交通工程学院,昆明650500 [2]河口瑶族自治县交通运输局,云南红河661300 [3]昆明理工大学信息工程与自动化学院,昆明650500

出　　处：《安全与环境学报》2025年第1期227-236,共10页Journal of Safety and Environment

基　　金：国家自然科学基金项目(62362044)。

摘　　要：在突发公共卫生事件封控情况下,大规模应急救援物资的配送需要兼顾效率、成本及安全性,在有限的救援投入下获取最大化资源利用和最小化配送成本,同时避免人员的交叉感染。为此,提出了基于两层配送网络的应急物资配送方案,并提出改进粒子群优化算法(Improved Particle Swarm Optimization Algorithm,IPSOA)对配送路径进行优化。首先,根据行政区划分以及物资需求点的空间分布、各需求点的居民人数和需求量,采用层次聚类算法建立由“物资储备中心-物资集散中心”和“物资集散中心-物资需求点”构成的两层配送网络,每层配送网络都由多配送中心和多需求点组成,该物资配送属于多配送车辆的多中心车辆路径规划问题(Multi-Depot Vehicle Routing Problem,MDVRP)。其次,为了获取合理高效的配送路径,以配送成本最小为目标,构建基于多约束的物资配送优化模型,并提出基于人工鱼群算法(Artificial Fish Swarm Algorithm,AFSA)的粒子群优化(AFSA-PSO)算法对两层配送网络进行求解。最后,以某市9个行政区在疫情封控期间的数据为例验证两层配送网络和AFSA-PSO算法的有效性。结果表明:构建的两层配送网络和AFSA-PSO算法能够对多车辆MDVRP问题进行有效求解,科学规划配送路径;算法对比发现,AFSA-PSO能够避免模型过早收敛,且能够获取比遗传算法和粒子群优化算法更少的车辆数和更短的配送路径,有效地降低配送成本,提高经济效益。During an unexpected public health emergency lockdown,the distribution of large-scale emergency relief supplies must strike a balance between efficiency,cost-effectiveness,and safety.Given constraints on rescue investments,optimizing resource utilization,reducing delivery expenses,and preventing cross-infection among personnel become imperative priorities.Thus,this study introduces an emergency materials distribution strategy employing a two-tier distribution network and an Improved Particle Swarm Optimization Algorithm(IPSOA)to enhance the efficiency of the distribution route.Initially,a hierarchical clustering algorithm is utilized to group data such as administrative regions,community locations,household numbers,population figures,and building statistics in each community.This process helps identify the material demands,establish the locations and quantities for material reserves,and designate distribution centers in every administrative region.Subsequently,a two-tier distribution network is constructed,comprising“material reserve centers to material distribution centers”and“material distribution centers to material demand points”.Each layer network comprises several distribution centers and numerous demand locations,thus presenting a Multi-Depot Vehicle Routing Problem(MDVRP)with multiple vehicles.To devise an effective and cost-efficient delivery plan,a multi-constraint delivery optimization model is formulated with the objective of minimizing the total delivery cost while adhering to constraints related to delivery distance and the number of vehicles used for delivery.Moreover,an enhanced Particle Swarm Optimization algorithm leveraging the Artificial Fish Swarm Algorithm(AFSA-PSO)is introduced to address and solve this optimization challenge.Finally,empirical data from 9 administrative districts in a specific city during epidemic lockdown periods is utilized as a case study to validate the efficiency of the two-tier distribution network and the AFSA-PSO algorithm.The practical findings demonstrate

关 键 词：公共安全 物资配送路径 改进粒子群优化算法 多车辆多中心车辆路径规划问题 分层聚类 公共卫生事件 

分 类 号：X95[环境科学与工程—安全科学]