系统仿真学报 ›› 2025, Vol. 37 ›› Issue (12): 3128-3139.doi: 10.16182/j.issn1004731x.joss.24-0705

• 论文 • 上一篇    

“货到人”系统订单拣选和分拣协同优化问题

任亮1,2, 周泽榕1, 马云峰1,2   

  1. 1.武汉科技大学 管理学院,湖北 武汉 430065
    2.武汉科技大学 服务科学与工程研究中心,湖北 武汉 430065
  • 收稿日期:2024-07-02 修回日期:2024-08-26 出版日期:2025-12-26 发布日期:2025-12-24
  • 通讯作者: 周泽榕
  • 第一作者简介:任亮(1985-),男,讲师,博士,研究方向为物流优化。
  • 基金资助:
    教育部人文社会科学(19YJA630054);湖北省教育厅哲学社会科学研究青年项目(20Q021);湖北省自然科学基金青年项目(2020CFB142);武汉科技大学资助项目(2022H20537)

Optimization of Order Picking and Sorting Coordintion inGoods-to-personSystem

Ren Liang1,2, Zhou Zerong1, Ma Yunfeng1,2   

  1. 1.School of Management, Wuhan University of Science and Technology, Wuhan 430065, China
    2.Institute of Service Science and Engineering, Wuhan University of Science and Technology, Wuhan 430065, China
  • Received:2024-07-02 Revised:2024-08-26 Online:2025-12-26 Published:2025-12-24
  • Contact: Zhou Zerong

摘要:

针对“货到人”系统中带时间窗的订单拣选和分拣协同问题,建立以分拣批次数量最小为目标的数学模型,结合问题特点提出基于“分类装载”策略的混合变邻域搜索算法(hybrid variable neighborhood search,HVNS)进行求解。数值实验结果表明:HVNS算法能够在缩短求解时间的前提下获得高质量的解;不同订单结构对分拣AGV装载能力的利用效果不同;在测试的实验环境下,通过与先拣选后分拣的传统作业模式相比,协同作业模式在完工时间上可以缩短约31%,在订单满足率上可以提升约38%。

关键词: “货到人”系统, 拣选分拣协同, 自动导引小车, 变邻域搜索算法, 时间窗

Abstract:

To improve the order picking and sorting collaboration with time windows in the "goods-to-person" system, a mathematical model aiming to minimize the number of sorting batches was established. With the characteristics of this issue considered, a hybrid variable neighborhood search (HVNS) algorithm based on the "classified loading" strategy was proposed for solutions. The numerical experimental results show that the HVNS algorithm can obtain high-quality solutions while shortening the solution time; different order structures have varying effects on the utilization of the loading capacity of sorting automated guided vehicles (AGVs); under the tested experimental conditions, the collaborative operation mode can reduce the makespan by approximately 31% and increase the order fulfillment rate by approximately 38% compared with the traditional operation mode of picking followed by sorting.

Key words: "goods-to-person" system, picking and sorting collaboration, automated guided vehicle, variable neighborhood search algorithm, time window

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