面向管材存储的自动化立体仓库货位优化  

Location optimization of automated storage and retrieval system for pipe storage

作　　者：屈新怀[1] 纪飞 丁必荣[1] 孟冠军[1] QU Xinhuai;JI Fei;DING Birong;MENG Guanjun(School of Mechanical Engineering,Hefei University of Technology,Hefei 230009,China)

机构地区：[1]合肥工业大学机械工程学院,安徽合肥230009

出　　处：《合肥工业大学学报（自然科学版）》2023年第1期1-5,共5页Journal of Hefei University of Technology：Natural Science

基　　金：国家重点研发计划资助项目(2019YFB1705303)。

摘　　要：文章以自动化立体仓库(automated storage and retrieval system,AS/RS)中管材的货位分配为研究对象,采用悬臂式货架进行存储,以存取效率、货架稳定性和货架平衡性为原则,建立多目标货位优化模型;设计粒子群算法(particle swarm optimization,PSO)和遗传算法(genetic algorithm,GA)的混合算法求解模型,使用MATLAB编程并运行汽车制管厂的实例数据进行仿真分析。结果表明,该文方法相较于传统PSO算法和GA算法具有一定的优越性,能够有效提高AS/RS的作业效率和货架安全性,对面向管材存储的AS/RS研究具有一定的理论和实践意义。Taking the distribution of pipes in the automated storage and retrieval system(AS/RS)as the research object,cantilever racks are used for storage.Based on the principles of storage efficiency,shelf stability and shelf balance,a multi-objective storage location optimization model is established.A hybrid algorithm of particle swarm optimization(PSO)and genetic algorithm(GA)is designed to solve the problem.MATLAB is used to program and run the example data of the automobile pipe factory for simulation analysis.The results show that compared with traditional PSO and GA algorithms,this method has certain advantages,and can effectively improve the operating efficiency and shelf safety of AS/RS.It also has certain theoretical and practical significance for the research on AS/RS for pipe storage.

关 键 词：自动化立体仓库(AS/RS) 货位优化 管材 悬臂式货架 多目标优化 

分 类 号：TH692.3[机械工程—机械制造及自动化]