基于两阶段狼群算法的自动化立体仓库作业集成优化  

Job Integrated Optimization of Automated Storage/retrieval Systems Based on Two-stage Wolf Pack Algorithm

作　　者：何李 陶翼飞[1] 罗俊斌 荀洪凯 HE Li;TAO Yifei;LUO Junbin;XUN Hongkai(Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming,650504;Kunming Logan-KSEC Airport System Company Ltd.,Kunming,650236)

机构地区：[1]昆明理工大学机电工程学院,昆明650504 [2]昆明昆船逻根机场系统有限公司,昆明650236

出　　处：《中国机械工程》2022年第21期2538-2546,共9页China Mechanical Engineering

基　　金：国家自然科学基金(51165014)。

摘　　要：为提高单载具自动化立体仓库动态工况下的进出库效率,针对自动化立体仓库作业集成优化问题建立了仿真优化模型。模型根据货物重质、出入库频率划分货架区域,以指令内最小化单载具堆垛机运行时间为研究目标,设计了一种两阶段狼群算法对其进行优化。该算法使用狼群算法对货位分配和作业调度进行集成优化,求解过程体现出两优化问题之间的关联和反馈。实验结果表明,在不同的订单规模下,相比其他优化方式,两阶段狼群算法能得到满意解,并有效缩短自动化立体仓库的作业时间。In order to improve the loading/unloading operation efficiency of single-shuttle AS/RS under dynamic working conditions,a simulation optimization model was established for the job integrated optimization problem of AS/RS.The model considered the weight of goods and the frequency of entering and leaving the warehouse to divide the rack area.To minimize the running time of single-shuttle stacker in the instruction,a two-stage wolf pack algorithm was designed.The algorithm used the wolf pack algorithm to optimize the storage location assignment and job scheduling,and the solution processes reflected the mutual connection and feedback between the two optimization problems.The experimental results show that under different order sizes,the two-stage wolf pack algorithm may obtain satisfactory solutions and effectively shorten the operation time of AS/RS,compared with other optimization methods.

关 键 词：自动化立体仓库 货位分配 作业调度 集成优化 两阶段狼群算法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]