Multi-objective optimization of electronic product goods location assignment in stereoscopic warehouse based on adaptive genetic algorithm
Multi-objective optimization of electronic product goods location assignment in stereoscopic warehouse based on adaptive genetic algorithm
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DOI：
10.1007/s10845-015-1177-7
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发表时间：
2015-11
影响因子：
8.3
通讯作者：
B. Yan;Chang-yuan Yan;Feng Long;Xingchao Tan
中科院分区：
文献类型：
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作者：
B. Yan;Chang-yuan Yan;Feng Long;Xingchao Tan
仓储是商品流通的重要组成部分。必须储存一定数量的物质，以满足一定时间内社会生产和消费的需要，以维持社会再生产过程的顺利进行。本研究主要研究电子产品在立体仓库存储时的仓储优化和货位分配。此外，本研究基于遗传算法的理论研究。本文以W公司LCM模组产品仓库现有仓库管理和货位分配为背景，采用随机库存的动态货位分配策略，构建了立体仓库的多目标货位分配模型。为了简化计算、提高效率，我们在实际数据的基础上，采用改进的遗传算子，通过改变权重系数转化为多目标优化，进行了Matlab仿真。自适应遗传算法可用于建立多目标货位分配模型，有效收敛于最优解。
Storage is an important part of commodity circulation. A certain amount of material must be stored to meet the needs of social production and consumption within a certain time to maintain the smooth process of social reproduction. This study focuses on warehousing optimization and goods location assignment when electronic products are stored in a stereoscopic storehouse. Moreover, this study is based on a theoretical study on genetic algorithm. On the basis of the background of the current warehouse management and cargo distribution of LCM module products warehouse belonging to W company, this study uses the dynamic goods location assignment strategy of stochastic inventory, and builds a multi-objective goods location assignment model of a stereoscopic warehouse. To simplify the calculations and improve the efficiency, we conduct a Matlab simulation on the basis of practical data by adopting a modified genetic operator and converting multi-objective optimization by the changing weight coefficient. The adaptive genetic algorithm can be used to make a multi-objective goods location assignment model that efficiently converges to the optimal solution.