工业工程 ›› 2022, Vol. 25 ›› Issue (4): 60-69,107.doi: 10.3969/j.issn.1007-7375.2022.04.008

• 专题论述 • 上一篇    下一篇

时变路网下电动冷藏车配送路径优化研究

王玖河1,2, 安聪琢1, 郭田宇3   

  1. 1. 燕山大学 经济管理学院,河北 秦皇岛 066004;
    2. 燕山大学 京津冀协同发展管理创新研究中心,河北 秦皇岛 066004;
    3. 辽宁工程技术大学 工商管理学院,辽宁 葫芦岛 125105
  • 收稿日期:2021-04-09 发布日期:2022-08-30
  • 作者简介:王玖河(1968—),男,吉林省人,教授,博士,主要研究方向为物流与供应链管理
  • 基金资助:
    河北社会科学基金资助项目(HB18GL075)

Optimization of Distribution Path of Electric Refrigerated Vehicle under Time-Varying Road Network

WANG Jiuhe1,2, AN Congzhuo1, GUO Tianyu3   

  1. 1. School of Economics and Management, Yanshan University, Qinhuangdao 066004, China;
    2. Center of Beijing-Tianjin-Hebei Cooperative Development Management Innovation Research, Yanshan University, Qinhuangdao 066004, China;
    3. School of Business Administration, Liaoning Technical University, Huludao 125105, China
  • Received:2021-04-09 Published:2022-08-30

摘要: 为了解决时变路网中电动车在冷链物流配送过程中的路径选择问题,根据冷链产品和电动冷藏车的特性,引入多模糊时间窗约束及配送车辆电量约束,建立时变路网下考虑充电站的多时间窗约束的电动冷藏车路径优化模型。运用AP聚类算法划分配送区域,在明确配送范围的基础上采用改进的遗传算法对模型进行求解。通过算例仿真,验证模型和算法的有效性和可行性,并将静态路网与时变路网下的配送方案进行对比,利用随机生成不同规模的案例对模型的普适性进行验证。结果表明,与静态路网相比,基于时变路网规划出的配送方案可以减少12.201%的配送成本。研究成果对于帮助企业科学的规划配送路径,降低配送成本等方面具有一定的指导意义。

关键词: 时变路网, 电动冷藏车, 多模糊时间窗, 遗传算法, AP聚类算法

Abstract: In order to solve the route selection problem of electric vehicles in the process of cold chain logistics distribution in time-varying road network, according to the characteristics of cold chain products and electric refrigerated vehicles, the multi-fuzzy time window constraints and the distribution vehicle power constraints are introduced, and the electric refrigerated vehicle route optimization model considering the multi-time window constraints of charging stations in time-varying road network established. The AP clustering algorithm is used to divide the distribution area, and the improved genetic algorithm used to solve the model on the basis of clear distribution range. The validity and feasibility of the model and algorithm are verified by a simulation example. The distribution schemes under static network and time-varying network are compared, and the universality of the model is verified by randomly generated cases of different scales. The results show that compared with the static road network, the distribution scheme based on time-varying road network can reduce the distribution cost by 12.201%. The research results have certain guiding significance for helping enterprises to plan the distribution route scientifically and reduce the distribution cost.

Key words: time-varying road network, electric refrigerated car, multiple fuzzy time windows, genetic algorithm, AP clustering algorithm

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