考虑充电调度的电动无人车配送路径规划问题研究  

Research on the distribution routing problem of electric unmanned vehicle considering charging scheduling

作　　者：曹珍 韩曙光[1] CAO Zhen;HAN Shuguang(School of Science,Zhejiang Sci-Tech University,Hangzhou 310018,China)

机构地区：[1]浙江理工大学理学院,杭州310018

出　　处：《浙江理工大学学报（自然科学版）》2023年第6期784-794,共11页Journal of Zhejiang Sci-Tech University(Natural Sciences)

基　　金：国家自然科学基金项目(12071436)。

摘　　要：在充电站有充电容量约束的情况下,研究充电调度电动无人车配送路径规划问题。首先以极小化车队中电动无人车的最大行驶距离为目标,构建数学规划模型,为电动无人车车队安排配送路径,使得各车的行驶距离尽可能均衡;其次应用动态规划算法(Dynamic programming algorithm,DP)求解小规模算例,改进遗传-模拟退火算法(Genetic-simulated annealing algorithm,GA-SA)优化较大规模算例的电动无人车路径和充电策略;最后对相关因素进行灵敏度分析,以验证所提出算法的可行性与合理性。结果表明:DP算法解小规模算例表现良好;改进GA-SA算法与单纯遗传算法(Genetic algorithm,GA)相比,求解大规模算例时优化的路径效果更佳,且大大缩短电动无人车车队的最长子路径的长度和总行驶距离。该研究可以为物流公司的电动无人车配送业务发展提供参考,帮助企业提高电动无人车的运输效率和服务水平,降低配送成本。Under the restriction that the charging station has charging capacity constraints,we focus on researching the distribution routing problem of electric unmanned vehicles with charge scheduling.A mathematical programming model was firstly established with the objective of minimizing the maximum travel distance of electric unmanned vehicles of the fleet,so as to arrange the distribution path for the unmanned vehicle fleet and balance the travel distance of each vehicle as much as possible.Secondly,dynamic programming(DP)algorithm was applied to solve small-scale examples,and genetic-simulated annealing algorithm(GA-SA)was improved to optimize the route and charging strategy of electric unmanned vehicles for large-scale examples.Finally,related factors were analyzed to verify the feasibility and rationality of the proposed algorithm.The results show that the DP algorithm performs well in solving small-scale examples.Compared with the simple genetic algorithm(GA),the improved GA-SA can get a more reasonable solution when solving large-scale examples,and greatly shorten the length of the longest sub-path and the total driving distance of the electric unmanned vehicle fleet.This study can provide reference for the development of electric unmanned vehicle distribution business of logistics companies,help enterprises improve the transportation efficiency and service level of electric unmanned vehicles,and reduce distribution costs.

关 键 词：电动无人车 配送路径规划 充电容量约束 充电调度 动态规划 遗传-模拟退火算法 

分 类 号：O223.1[理学—运筹学与控制论] O223.4[理学—数学]