货位优化及堆垛机路径优化协同研究  

Collaborative Research on Cargo Level Optimization and Stacker Path Optimization

作　　者：范英 吕志赛 陈熙 高思伟 FAN Ying;LV Zhi-sai;CHEN Xi;GAO Si-wei(School of Transportation and Logistics,Taiyuan University of Science and Technology,Taiyuan 030024,China)

机构地区：[1]太原科技大学交通与物流学院,太原030024

出　　处：《太原科技大学学报》2024年第4期415-420,共6页Journal of Taiyuan University of Science and Technology

基　　金：山西省重点研发计划(201903D121176)。

摘　　要：自动化立体仓库是一个错综复杂的存储系统,堆垛机出入库作业时间直接影响自动化立体仓库的工作效率。针对自动化立体仓库的堆垛机出入库路径优化问题,提出先利用ABC分类法对货物进行分类,以此为依据进行货位优化,在此基础上,建立堆垛机出入库路径优化模型,并采取改进的遗传算法对优化模型进行仿真。最后对仿真结果及货位优化前的结果进行对比分析,货位优化后出入库时间减少了11.7%,而堆垛机路径优化后,总运行时间又下降了12.0%.结果证明,先进行货位优化再对堆垛机路径进行优化是提高货物出入库效率的一种有效方法。The automated three-dimensional warehouse is an intricate storage system,and the stacker crane access operation time directly affects the efficiency of the automated three-dimensional warehouse.In order to optimize the access path of stacker crane in the automated warehouse,we propose to use ABC classification method to classify the goods first,and then use it as the basis for cargo level optimization,based on which,we establish a stacker crane access path optimization model,and adopt a genetic algorithm to simulate the optimization model.Finally,the simulation results and the results before the optimization of cargo level are compared and analyzed.The access time is reduced by 11.7%after the optimization of cargo level,and the total running time is reduced by 12.0%after the optimization of stacker path.The results prove that the first row of cargo position optimization and then using genetic algorithm to solve the stacker path is an effective way to improve the efficiency of cargo entry and exit.

关 键 词：货位优化 路径优化 改进的遗传算法 ABC分类法 

分 类 号：U4[交通运输工程—道路与铁道工程]