Scheduling optimization of multi-deep four-way shuttle warehousing system

被引：0
|
作者：
Zhan X. [1 ]
Xu L. [1 ]
Ling X. [2 ]
Chen C. [1 ]
机构：
[1] School of Mechanical Engineering, Tongji University, Shanghai
[2] School of Artificial Intelligence, Shanghai Normal University Tianhua College, Shanghai
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 08期
基金：
中国国家自然科学基金;
关键词：
improved hybrid genetic algorithm; multi-deep four-way shuttle warehousing system; operating efficiency; route orientation; scheduling optimization;
D O I：
10.13196/j.cims.2022.08.020
中图分类号：
学科分类号：
摘要：
At present, the multi-deep four-way shuttle warehousing system has problems such as multiple four-way shuttle conflicts and deadlocks, which cause the blockage of inbound and outbound tasks, affecting the overall efficiency of the system. Hopcroft-Tarjan algorithm was used to formulate route orientation strategy for the multi-deep storage area. A scheduling optimization model with the goal of minimum operating time was established, and an Improved Hybrid Genetic Algorithm (IHGA) was designed to solve the optimization model. The adjustment of coding and the improvement of mutation repair mechanism could effectively avoid the problem of illegal solutions in the iterative process. A multi-position neighborhood exchange method based on task sorting was proposed for increasing the diversity of the solution space effectively. The case study showed that the route orientation strategy could effectively avoid conflicts and deadlocks and improve system operation efficiency. Meanwhile, the IHGA had faster convergence speed and higher optimization efficiency, which could effectively shorten the time of inbound and outbound operations and improve the efficiency of inbound and outbound scheduling. © 2022 CIMS. All rights reserved.
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页码：2496 / 2507
页数：11
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