新能源移动充电车路径优化问题研究  

Studyon Routing Problem for New Energy Mobile Charging Vehicles

作　　者：陈萍[1] 董文哲 于信尧 CHEN Ping;DONGWen-zhe;YU Xin-yao(Business School,Nankai Univeristy,Tianjin 300071,China;Bartlett School,University College London,London WC1E 6BT,UK)

机构地区：[1]南开大学商学院,天津300071 [2]伦敦大学巴特莱特学院,伦敦WC1E 6BT

出　　处：《运筹与管理》2020年第2期12-18,共7页Operations Research and Management Science

基　　金：国家自然科学基金青年科学基金项目(71701107);教育部人文社会科学青年基金项目(13YJC630010)。

摘　　要：在绿色城市背景下,新能源汽车的数量快速增长,现有公共充电设施的不完善使得移动充电服务应运而生.投入运营成本较高而利润低成为阻碍移动充电业务运营的瓶颈之一,如何通过科学合理的调度提高平台利润成为重要问题.本文研究了移动充电车队的调度和路径优化问题,以平台最大收益为目标,综合考虑顾客软时间窗、移动电池容量以及充电车续航里程等约束,建立数学规划模型;设计了一种最大最小蚁群算法,并通过数值实验验证了模型的合理性和算法的有效性,为移动充电企业运营提供决策参考.Against the background of green city,the number of electricvehicles has increased sharply.However,the charging infrastructure is notsufficient,and thus mobile charging industryappears.However,these companies are not profitableas expected.The main problem they are facing is the conflict between high operating cost and low profits.Optimizing the decision making of mobile charging vehicle routing becomes a critical issue.This study focuses on mobile charging vehicle routing problem,which aims to maximize the total profit under the con-straints of soft time windows,battery capacity and endurance mileage.We formulate this problem.In addition,to solve this problem,a max-min ant colony algorithm is presented.Computational results demonstrate the effec-tiveness and efficiency of the model and algorithm.This paper also provides some managerial insights for mobile charging companies operation.

关 键 词：新能源车 路径优化 软时间窗 电池最大容量 续航里程 最大最小蚁群算法 

分 类 号：O224[理学—运筹学与控制论]