工业工程 ›› 2019, Vol. 22 ›› Issue (3): 52-56.doi: 10.3969/j.issn.1007-7375.2019.03.007

• 专题论述 • 上一篇    下一篇

共享电动车电池配送问题研究

冯春1,2, 秦冰芳1, 叶露1   

  1. 1. 西南交通大学 交通运输与物流学院, 四川 成都 610031;
    2. 西南交通大学 综合交通运输智能化国家地方联合工程实验室, 四川 成都 610031
  • 收稿日期:2018-10-27 出版日期:2019-06-30 发布日期:2019-06-27
  • 作者简介:冯春(1970-),男,四川省人,教授,博士,主要研究方向为物流与供应链管理
  • 基金资助:
    国家社会科学基金资助项目(17BGL085)

A Research on Distribution Problem of Electric Bicycle-sharing Batteries

FENG Chun1,2, QIN Bingfang1, YE Lu1   

  1. 1.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China;
    2. National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2018-10-27 Online:2019-06-30 Published:2019-06-27

摘要: 共享电动车电池的配送方案关系到用户的切身体验和企业利益。为制定最优配送方案,真正打通人们出行的“最后一公里”,本文考虑企业对成本的要求和用户对时效性的要求,以总配送成本最小以及用户满意度最高为目标建立了一个带软时间窗的车辆路径问题模型,利用扫描法和基于最佳路径成本的交叉算子改进了传统遗传算法,用算例验证了模型与改进算法的有效性,并通过数值实验找出了种群大小、迭代次数与最优解之间的相关关系。

关键词: 共享电动车电池配送, 带软时间窗的车辆路径问题, 扫描算法, 遗传算法

Abstract: The distribution plan of electric bicycle-sharing batteries has a great impact on the users' immediate experience and the interests of the company. In order to develop an optimal distribution scheme and truly get through "the last mile" of people's travel, the requirements of enterprises for the distribution cost and the users' requirements for timeliness are considered, and a model of vehicle routing problem with soft time windows with objectives of minimizing the total distribution cost and maximizing user satisfaction is established. Then the traditional genetic algorithm is improved by sweep algorithm and the crossover operator based on the cost of optimal path. Finally, an example is adopted to verify that this model and the improved algorithm are effective. And the correlation between population size, iteration number and optimal solution is found by numerical experiments.

Key words: distribution problem of electric bicycle-sharing batteries, vehicle routing problem with soft time windows, sweep algorithm, genetic algorithm

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