工业工程 ›› 2021, Vol. 24 ›› Issue (5): 72-76.doi: 10.3969/j.issn.1007-7375.2021.05.009

• 专题论述 • 上一篇    下一篇

带时间窗的同时取送货车辆路径问题求解算法

闫军1, 常乐2, 王璐璐2, 赵彤3   

  1. 1. 兰州交通大学 甘肃省物流与信息技术研究院,甘肃 兰州 730070;
    2. 兰州交通大学 机电技术研究所,甘肃 兰州 730070;
    3. 呼和浩特铁路局集团公司包头货运中心,内蒙古 包头 014000
  • 收稿日期:2020-04-08 发布日期:2021-11-02
  • 作者简介:闫军(1971—),男,甘肃省人,高级工程师,硕士,主要研究方向为协同物流及动态规划
  • 基金资助:
    甘肃省自然科学基金资助项目(148RJZA049);甘肃省教育厅战略研究资助项目(2018F-08)

A Solution Algorithm for the Problem of Taking Delivery Vehicle Path at the Same Time with Time Window

YAN Jun1, CHANG Le2, WANG Lulu2, ZHAO Tong3   

  1. 1. Gansu Institute of Logistics and Information Technology;
    2. Mechatronics T&R-Institute, Lanzhou Jiaotong University, Lanzhou 730070, China;
    3. Baotou Freight Center, Hohhot Railway Bureau Group Company, Baotou 014000, China
  • Received:2020-04-08 Published:2021-11-02

摘要: 为了整合物流配送过程的退货与送货服务,依据实际情况建立带时间窗的同时取送货车辆路径规划模型,设计一种基于K-means聚类处理的Q-Leaning自启发式蚁群算法解决此类问题。根据配送服务的特性,在基本的K-means算法上作相应的改进,同时提高蚁群算法的局部搜索能力,完成两算法的合理衔接。选用相关文献数据和标准算例进行实验,验证所提算法具有较好的性能,可以解决所描述的此类问题。

关键词: 车辆路径问题, 取送货问题, 时间窗, 蚁群算法

Abstract: In order to integrate the return and delivery service in the process of logistics and distribution, a vehicle routing model with time window is established according to the actual situation, and a Q-learning self-heuristic ant colony algorithm based on K-means clustering processing is designed to solve such problems. According to the characteristics of distribution service, by improving the basic k-means algorithm, the local search ability of the ant colony algorithm is improved, and the reasonable connection of the two algorithms completed. Experiments are carried out according to the relevant literature data and standard examples to verify that the proposed algorithm has good performance and can solve the described problems.

Key words: vehicle routing problem, pickup and delivery problem, time windows, ant colony algorithm

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