运筹与管理 ›› 2020, Vol. 29 ›› Issue (2): 12-18.DOI: 10.12005/orms.2020.0029

• 理论分析与方法探讨 • 上一篇    下一篇

新能源移动充电车路径优化问题研究

陈萍1, 董文哲2, 于信尧1   

  1. 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
  • 收稿日期:2018-08-21 出版日期:2020-02-25
  • 作者简介:陈萍(1981-), 女, 山东人, 博士, 讲师, 研究方向:城市物流, 车辆优化调度;董文哲(1996-), 女, 河北人, 硕士生, 研究方向:城市物流, 车辆优化调度;于信尧(1996-), 男, 辽宁人, 硕士生, 研究方向:车辆优化调度, 信息系统。
  • 基金资助:
    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)

Studyon Routing Problemfor New Energy Mobile Charging Vehicles

CHEN Ping1, DONGWen-zhe2, YU Xin-yao1   

  1. 1. Business School, Nankai Univeristy, Tianjin 300071, China;
    2. Bartlett School, University College London, London WC1E 6BT, UK
  • Received:2018-08-21 Online:2020-02-25

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。

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

Abstract: 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 constraints 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 effectiveness and efficiency of the model and algorithm. This paper also provides some managerial insights for mobile charging companies operation.

Key words: new energy vehicle, routing, Soft time windows, battery capacity, endurance mileage, max-min ant system

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