S冷链物流中心的储位规划与补货策略优化

Storage Planning and Replenishment Strategy Optimization of S Cold Chain Logistics Center

随着科技的快速发展,智慧化物流技术开创了仓储的新阶段。当前仓库系统规模庞大、存储货物种类繁多,因此,需要借助数字化技术对仓储载体及对象进行规划、设计,实现低成本、高效率的运行状态。基于S冷链物流中心存储与补货策略的相关数据,文中运用双标准ABC分类法及Apriori算法对商品相关性进行数据挖掘,进而对储位规划与补货策略进行优化与设计,提升了仓库的利用率,降低了仓储整体成本。

With the rapid development of science and technology,intelligent logistics technology has created a new stage of warehousing.The current warehouse system has a large scale and a wide variety of stored goods,so it is necessary to use digital technology to plan and design the storage carrier and object,so as to achieve low cost and high efficiency.Based on the relevant data of storage and replenishment strategy of S cold chain logistics center,this paper uses double-standard ABC classification and Apriori algorithm to carry out data mining for commodity correlation,and then optimizes and designs the storage location planning and replenishment strategy,which improves the utilization rate of the warehouse and reduces the overall storage cost.