基于遗传算法的两阶段应急物流配送中心选址研究

Research on Location of Two-Stage Emergency Logistics Distribution Center Based on Genetic Algorithm

针对考虑需求紧迫度不同、救援时间和选址成本等多种因素下的应急物流配送中心选址问题,采用两阶段法进行研究。第一阶段采用灰色关联分析法与TOPSIS法相结合,对物流备选中心进行优先级评价;第二阶段建立考虑需求紧迫度的选址数学模型,以汶川地震为例,运用遗传算法进行求解。同不考虑紧迫度的选址结果进行对比,结果表明考虑需求紧迫度时的重灾区域物资配送时间相对缩短了16.65%,并且可以实现优先救援目标,减少了总救援成本的同时提高了整体的应急物资配送效率,进一步验证了该模型选址方案兼具救援时效性和公平性。

A two-stage method is used to study the location problem of emergency logistics distribution centers considering various factors such as different demand urgency,rescue time,and location costs.In the first stage,the gray correlation analysis method and TOPSIS method are combined to evaluate the priority of logistics alternative centers;In the second stage,a mathematical model of location selection considering the urgency of demand was established,and a genetic algorithm was used to solve the Wenchuan earthquake as an example.Compared with the results of location selection without considering urgency,the results show that the time for material distribution in the severely affected areas when considering demand urgency is relatively reduced by 16.65%,and it can achieve the priority rescue goal,reduce the total rescue cost,and improve the overall efficiency of emergency material distribution,further verifying that the model location scheme combines rescue timeliness and fairness.