基于SKU关联度的储位优化问题研究  

Research on Optimization of Storage Location Based on SKU Correlation

作　　者：包菊芳[1] 王丽 BAO Ju-fang;WANG Li(School of Management Science and Engineering,Anhui University of Technology,Maanshang 243002,China)

机构地区：[1]安徽工业大学管理科学与工程学院,安徽马鞍山243002

出　　处：《数学的实践与认识》2021年第14期31-40,共10页Mathematics in Practice and Theory

基　　金：安徽省高校人文社科重大项目(SK2015ZD08)。

摘　　要：在"货到人"智能仓库中的储位分配问题中,优化储位分配策略是提高订单拣选速度和仓库运作效率的关键环节.在考虑了SKU间关联度的基础上,设定以同一货架上SKU的总关联度最大为目标建立数学模型,并设计了模型求解的智能算法.首先根据历史订单采用FP-Growth算法计算出SKU间的关联度;然后以货架储位数为阈值将相关性高的SKU聚集形成一个品项簇,生成SKU聚类结果作为储位分配的优化结果.通过实际案例进行分析,得出在本文算法策略下移动货架搬运次数相比随机储位策略减少了26.27%,大大提高了订单出库效率.In the storage space allocation problem in the"goods-to-person"intelligent warehouse,optimizing the storage space allocation strategy is a key link to improve the order picking speed and warehouse operation efficiency.On the basis of considering the correlation between SKUs,this article sets the goal of establishing a mathematical model with the maximum total correlation of SKUs on the same shelf,and designs an intelligent algorithm for model solving.First,the FP-Growth algorithm is used to calculate the correlation between SKUs based on historical orders;then the high-relevant SKUs are aggregated to form an item cluster using shelf storage as a threshold,and SKU clustering results are generated as the optimization result of storage allocation.Through the analysis of actual cases,it is concluded that the number of moving racks under the algorithm strategy of this paper is reduced by 26.27%compared with the random storage strategy,which greatly improves the efficiency of order delivery.

关 键 词：货到人智能仓库 储位分配 关联度 FP-GROWTH算法 

分 类 号：F274[经济管理—企业管理] TP18[经济管理—国民经济]