基于通用变邻域搜索的多AGV分拣调度优化
DOI:
作者:
作者单位:

1.宜宾职业技术学院;2.西南交通大学

作者简介:

通讯作者:

中图分类号:

基金项目:


A general variable neighborhood search for the multi-AGV scheduling problem with sorting operations
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    物流仓储分拣中心采用多台AGV对大量包裹进行快速分拣。在考虑作业时间窗和充电需求的基础上,如何为各台小车指定转运作业和排序成为分拣调度的关键。为了实现对大规模调度问题的求解,以最小化分拣作业周期为目标提出了一种通用变邻域搜索算法。该算法采用遍历插入的启发式策略生成初始解,结合十种邻域操作算子实现邻域解生成。使用不同规模的算例进行计算分析,结果表明了较之混合整数规划模型和约束规划模型,所提出的GVNS算法具有计算时间和求解性能方面的优势,同时分析了不同的AGV充电速率和数量配置对分拣效率的影响。本文的研究有助于提高物流分拣效率,扩充了多AGV调度优化方法。

    Abstract:

    Lots of packages are sorted quickly by using multiple automatic guided vehicles (AGVs) in the logistics sorting centers. With the consideration of power consumption and charging demand of the AGVs, how to determine the assignment of transferring packages to AGVs and the sequence of sorting tasks for each AGV is the key to the sorting operation. In order to solve the large-sized problem instances, this paper proposes a general variable neighborhood search (GVNS) algorithm to minimize the sorting operation makespan. The GVNS algorithm adopts traversal insertion heuristic to generate the initial solution, and uses ten neighborhood operator to obtain the neighbor solutions. Different scaled test instances are used to analyze the performance of the proposed GVNS. Compared with mixed integer programming model and constraint programming model, the GVNS performs better, in terms of solution time and solution quality. Moreover, the impacts of the sorting efficiency are also analyzed when considering the AGVs with different charging speed and different available quantity. This work is helpful to improve the efficiency of logistics sorting, enrich the research content of multi-AGV scheduling.

    参考文献
    相似文献
    引证文献
引用本文
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2021-08-20
  • 最后修改日期:2021-08-22
  • 录用日期:2022-04-26
  • 在线发布日期:
  • 出版日期:
文章二维码