系统仿真学报 ›› 2024, Vol. 36 ›› Issue (3): 564-577.doi: 10.16182/j.issn1004731x.joss.23-0422

• 论文 • 上一篇    下一篇

考虑拆分策略的智能仓库订单分拣建模与优化

徐毓泽1(), 张林鍹1,2(), 李惠3, 葛明4, 何莞依4   

  1. 1.新疆大学 电气工程学院, 新疆 乌鲁木齐 830000
    2.清华大学 自动化系, 北京 100089
    3.中央财经大学 信息学院, 北京 102206
    4.香港工业人工智能及机械人研发中心, 香港 999077
  • 收稿日期:2023-04-07 修回日期:2023-06-13 出版日期:2024-03-15 发布日期:2024-03-14
  • 通讯作者: 张林鍹 E-mail:1072979947@qq.com;lxzhang@mail.tsinghua.edu.cn
  • 第一作者简介:徐毓泽(1996-),男,硕士生,研究方向为生产计划排程、物流分拣。E-mail:1072979947@qq.com
  • 基金资助:
    国家重点研发计划(2018YFB1703103);香港创科平台InnoHK资助项目(20213000116);新疆维吾尔自治区研究生科研创新项目(XJ2022G042)

Modeling and Optimization of Smart Warehouse Order Sorting Considering Splitting Strategy

Xu Yuze1(), Zhang Linxuan1,2(), Li Hui3, Ge Ming4, He Wanyi4   

  1. 1.School of Electrical Engineering, Xinjiang University, Urumqi 830000, China
    2.Department of Automation, Tsinghua University, Beijing 100089, China
    3.School of Information, Central University of Finance and Economics, Beijing 102206, China
    4.Hong Kong Industrial Artificial Intelligence and Robotics Centre, Hong Kong 999077, China
  • Received:2023-04-07 Revised:2023-06-13 Online:2024-03-15 Published:2024-03-14
  • Contact: Zhang Linxuan E-mail:1072979947@qq.com;lxzhang@mail.tsinghua.edu.cn

摘要:

针对一种两类订单混合分拣的自动小车分拣问题,考虑其在订单分拣过程中出现的分拣AGV(automatic guided vehicle)堵塞和人工收集站闲置的现象,提出一种订单拆分的策略及拆分后子订单批次调整的方法,并以总订单完工时间最小化为优化目标,建立了订单拆分的订单分拣整数规划模型;提出一种改进离散灰狼优化算法,将订单分批、批次排序以及下架库位选取3个子问题进行联合优化。数值实验结果表明,订单拆分策略使总订单完工时间显著减少,并且通过与经典算法以及其他同类型算法的对比,验证了所提算法的优越性。

关键词: 订单拆分, 订单分批, 批次排序, 离散灰狼优化算法, 自动小车分拣系统

Abstract:

For an automatic vehicle sorting problem involving mixed sorting of two types of orders, an order splitting strategy and a method for batch adjustment of sub-orders after splitting are proposed by considering the phenomena of blockage of automatic guided vehicles (AGVs) and idleness of manual collection stations in the order sorting process. In addition, with the optimization objective of minimizing the total order completion time, an order sorting integer planning model with order splitting is established. An improved discrete grey wolf optimization algorithm is proposed to jointly optimize the three sub-problems of order batching, batch sorting, and product unloading location selection. Numerical experimental results show that the order splitting strategy leads to a significant reduction in the total order completion time, and the superiority of the proposed algorithm is verified by comparing it with the classical algorithm and other algorithms of the same type.

Key words: order splitting, order batching, batch sorting, discrete grey wolf optimization algorithm, automatic vehicle sorting system

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