改进遗传算法在自动化立体仓库货位分配中的应用  

Research on Application of Automated Storage and Retrieval System Slotting Optimization Based on Improved Genetic Algorithm

作　　者：赵阳 ZHAO Yang(School of Mechanical and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学机电工程学院

出　　处：《物流工程与管理》2020年第2期53-56,49,共5页Logistics Engineering and Management

摘　　要：现今电子商务技术和物流行业快速发展,作为物流系统的关键环节,自动化立体仓库的使用效率对行业整体效益起着关键作用,其中的核心就是货位优化。文中将自动化立体仓库作为研究对象,对物品在仓库中存储的货位选择策略进行了优化研究,提出一种改进遗传算法。文中以提高货架稳定性、提高货物出入库效率等自动化立体仓库的基本使用原则为优化目标,对货位优化的多目标优化问题进行建模;然后通过对比基本遗传算法和双种群遗传算法,采用双种群遗传算法求解数学模型;最后使用MATLAB工具仿真,实验结果验证了算法的有效性。With the rapid development of e-commerce technology and logistics industry,the use efficiency of Automated Storage and Retrieval System plays a vital role in the overall efficiency of the industry,the core of which is location optimization.In this paper,the Automated Storage and Retrieval System is taken as the research object,and the cargo location selection strategy in the warehouse is optimized.In order to improve the stability of the shelves and the efficiency of the cargoes in and out of the warehouse,this paper models the multi-objective optimization problem of the location optimization.Then,by comparing the basic genetic algorithm and the dual population genetic algorithm,the dual population genetic algorithm is used to solve the mathematical model.Finally,the Matlab tool is used to simulate and the experimental results verify the validity of the algorithm.

关 键 词：自动化立体仓库 货位优化 多目标优化 双种群遗传算法 

分 类 号：F251[经济管理—国民经济]