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考虑并行移动的PBS系统取货时间最优改进

马云峰1,杨习杰2,余玉刚3,任亮1   

  1. 1. 武汉科技大学
    2. 武汉科技大学恒大管理学院
    3. 中国科学技术大学管理学院
  • 收稿日期:2022-03-14 修回日期:2022-06-19 发布日期:2022-09-02
  • 通讯作者: 余玉刚
  • 基金资助:
    多用户多信道认知无线电网络的资源分配的研究;区域经济多极网络空间组织理论与实证研究

Optimal improvement of retrieval time for PBS system by considering parallel movement

  • Received:2022-03-14 Revised:2022-06-19 Published:2022-09-02

摘要: 基于拼图的存储系统(Puzzle-based Storage System,PBS系统),是一种新兴的密集存储系统,系统内每个存储单元模块是空的或者存有货物,每个货物可以移动到相邻的空货位中。在单步移动假设下,现有的精确算法和启发式算法已经实现了取货过程中的移动步数最小,但却未能有效优化取货时间这一影响系统吞吐量的关键指标。针对多空位PBS系统单任务取货问题,在现有算法解的基础上,设计了基于并行移动的最优算法,即保持移动成本不变的前提下减少取货过程的时间消耗。在不同系统布局下通过大量算例进行了数值实验,结果发现:并行移动在取货时间上平均优化10%以上,随着系统规模的增大,优化的比例逐渐增加,但其边际值是递减的;非目标货物的移动次数和空位实际使用数量是影响并行移动的主要因素;算法在中小规模问题中表现良好的计算性能。

关键词: 自动化仓库, PBS系统, 取货时间, 并行移动, 最优算法

Abstract: Puzzle-based storage (PBS) is an emerging compact storage system where each cell is empty or occupied by an item, and each item can be moved to its adjacent empty cells. Under the single-load movement assumption, some existing exact and heuristic algorithms have enabled the minimum number of moves for the single-item retrieval problem in a puzzle-based storage system with multiple escorts (SRPME). Nevertheless, they failed to effectively optimize the retrieval time, which is a critical indicator of system throughput. In this article, both movement cost and retrieval time are taken into account in the SRPME. Based on a solution obtained by the existing algorithms for solving the single-item retrieval problem in PBS system with multiple escorts, an optimal algorithm considering parallel movement is designed, that is, to reduce the moving time of the item retrieval while keeping the number of item-moves unchanged. The proposed algorithm is based on the idea of implicit enumeration, and it only judges the parallelism between the first move of each escort during each iteration. Extensive numerical experiments were used to evaluate the impact of parallel movement and the algorithm’s performance, where the system size of the instances ranged from 4×4 to 30×30. The results show that the parallel movement saves an overall of more than 10% in retrieval time, and the number of O-move and the actual number of escorts used are the main factors affecting parallel movement. The average optimization ratio increases as the size of the system grows, while its marginal value decreases. The proposed method has good computational performance in small to medium-size issues, which can be seen as a good choose in a large variety of future applications of the PBS systems.

Key words: automated warehouse, Puzzle-based storage system, retrieval time, parallel movement, optimal algorithm