摘要
灾难中的应急援助对于拯救生命和减轻人类痛苦至关重要。为了最大限度地减少由于延迟获得服务而造成的区域公平性感知成本、心理痛苦成本和运输采购成本,提供了一种考虑多物资的三目标优化模式,该模式集成了多配送中心、多需求点的路径规划,应用多目标粒子群(MOPSO)算法进行问题求解,并以汶川地震为例进行模型验证。结果显示:相较于单独运输单物资,同时运输多物资调度的心理公平性更高,灾民痛苦程度更低;相对于传统运输方案,考虑公平性感知方案下资源利用更有效;灾后短时间内食品和饮用水的供应紧迫度略高于医药包。
Emergency assistance in disasters is crucial for saving lives and alleviating human suffering.In order to minimize the perceived cost of regional equity,the cost of psychological distress and the cost of transportation procurement due to delayed access to services,a three-objective optimization model considering multiple goods was provided,the model integrated multi-distribution center and multi-demand point path planning,applied multi-objective particle swarm optimization algorithm to solve the problem,and studied the Wenchuan earthquake case to verify the proposed model.The results showed that the psychological fairness of multi-goods transportation is higher than that of single goods transportation,and the suffering degree of disaster victims is lower,considering equity perception scheme is a more efficient use of resources than traditional transport scheme and food and potable water supplies are slightly more urgent than medical kits in the short term after a disaster.
作者
熊伊宁
周心怡
XIONG Yining;ZHOU Xinyi(School of Safety Science and Emergency Management,Wuhan University of Technology,Wuhan 430070,China;不详)
出处
《武汉理工大学学报(信息与管理工程版)》
CAS
2024年第4期534-541,共8页
Journal of Wuhan University of Technology:Information & Management Engineering
基金
国家社科基金重大项目(21&ZD127).
关键词
应急物流
心理代价
公平性感知
多物资配送
粒子群算法
emergency logistics
psychological cost
fairness perception
multi-material distribution
particle swarm optimization algorithm