广东工业大学学报 ›› 2013, Vol. 30 ›› Issue (1): 61-67.doi: 10.3969/j.issn.1007-7162.2013.01.011

• 综合研究 • 上一篇    下一篇

带有时间窗的虚拟场站接驳补货车辆路径问题

谢桂芩1,2,杨玉华3,涂井先4   

  1. 1.广东工业大学 应用数学学院,广东 广州,510520; 2.罗定中学,广东 云浮,527200; 3.广西工学院 鹿山学院,广西 柳州,545616; 4. 福州大学 数学与计算机科学学院,福建 福州,350108
  • 收稿日期:2012-04-16 出版日期:2013-03-30 发布日期:2013-03-30
  • 作者简介:谢桂芩(1984-),女,硕士研究生,主要研究方向为多目标进化算法.
  • 基金资助:

    广东省自然科学基金资助项目(10251009001000002)

The LinehaulFeeder Vehicle Routing Problem with Time Windows and Virtual Depots

Xie Gui-qin1,2, Yang Yu-hua3, Tu Jing-xian4   

  1. 1. Faculty of Applied Mathematics, Guangdong University of Technology, Guangzhou 510520,China;2.Louding Middle School, Yunfu 527200,China;3. Lushan College,  Guangxi University of Technology, Liuzhou 545616,China; 4. College of Mathematics and Computer Science,Fuzhou University,  Fuzhou 350108, China
  • Received:2012-04-16 Online:2013-03-30 Published:2013-03-30

摘要: 针对大区域多需求点的物流配送系统,在原有的车辆配送总费用为目标的基础上,兼顾顾客的满意度目标,建立了带有时间窗车辆路径问题的多目标最优化模型,该模型基于大小车沿途在虚拟场站接驳补货策略,节省了货车往返配送中心补货次数、距离与时间.根据该模型需要部分顾客作补货点的特点,利用K均值聚类的方法将顾客分类,采用基于分区域和极大极小策略的多目标进化算法思想进行求解,以测试题库The VRP Web中的算例进行测试分析.经由测试结果比较,相较于非接驳补货的传统VRPTW,该模型效益明显.

关键词: 虚拟场站; 接驳补货; 车辆路径问题; 多目标优化; 多目标进化算法

Abstract: On the basis that in original literature minimum vehicle scheduling cost was set as the only objective, it sets the maximum customer satisfaction index as another objective, and proposes a mathematical model for the linehaul-feeder multi-objective vehicle routing problem with time windows and virtual depots . The new model economizes the replenishment number of round trips, distance and time. K-means clustering method was applied to select some customers as the replenishment points, the problem was solved through the multi-objective evolutionary algorithm, based on sub-regions and the max-min strategy, and some instances were tested in the VRP web question bank. The experimental results show that the proposed model is more effective than the traditional non linehaul-feeder VRPTW.

Key words: virtual depot;linehaul feeder;Vehicle Routing Problem (VRP); multiobjective optimization; multiobjective evolutionary algorithm

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