基于进化算法的电动物流车辆配送路径优化算法研究  

Research on Optimization Algorithm for Delivery Routing of Electric Logistics Vehicles Based on Evolutionary Algorithm

作　　者：余法红 崔华 陈梅佳 朱冬平 YU Fahong;CUI Hua;CHEN Meijia;ZHU Dongping(Center of Intelligent Computing and Security Research,Shanwei Institute of Technology,Shanwei 516600,China;Suzhou Vocational University,Suzhou 215104,China)

机构地区：[1]汕尾职业技术学院智能计算及安全研究中心,广东汕尾516600 [2]苏州市职业大学,江苏苏州215104

出　　处：《现代信息科技》2025年第6期75-82,共8页Modern Information Technology

基　　金：广东省普通高校重点科研平台项目(2024CJPT004);广东省普通高校特色创新类项目(2023KTSCX351);广东省高职教育教学改革研究与实践项目(2023JG511);广东省教育科学规划项目(2023GXJK946)。

摘　　要：针对物流配送中存在客户分布散乱及电动车续航等问题,文章设计了一个电动物流车线路优化算法用于求解电动车辆路径问题(Electric Vehicle Routing Problem,EVRP)。根据电动物流车的问题建立了EVRPTW问题的模型,从最终的配送成本出发,获得在电量、载重量以及客户时间窗等约束下成本尽可能小的解。在ERVPTW的模型基础上使用遗传算法,随机生成初始种群,在交叉、变异等过程当中保证求得解的复杂度。以嘉兴物流路径规划为例,经实际验证,所设计的方法具备有效性。In response to the problems of scattered customer distribution and electric vehicle range in logistics and distribution,this paper designs an electric logistics vehicle routing optimization algorithm to solve the Electric Vehicle Routing Problem(EVRP).Based on the problem of electric logistics vehicles,a model of the EVRPTW problem is established.Starting from the final distribution cost,the model solution with the lowest possible final cost is obtained under the constraints of electricity,load capacity,and customer time window.Based on the model of EVRPTW,it uses the Genetic Algorithm to randomly generate initial population,and ensures the complexity of the solution in the crossover,mutation,and other processes.Taking Jiaxing logistics routing planning as an example,the designed method is effective after practical verification.

关 键 词：车辆配送 路径优化 进化算法 遗传算法 

分 类 号：G202[文化科学—传播学]