考慮需求相依性之移動貨架倉儲系統儲位管理方法

Abstract

This thesis develops the Summed Correlation Assignment Algorithm (SCAA) to solve the Storage Location Assignment Problem (SLAP) in rack-moving mobile robots warehouses (RMWs). The combination of goods stored on the inventory pods mainly influences the warehouse workload. As a shared storage policy, in which each product is stored on multiple inventory pods, is applied, every inventory pod only holds few items of its products. The proposed algorithm combines several heuristics, to manage the replenishment process of products on inventory pods. A computational study is conducted to simulate warehouse operations under changing warehouse parameters and control policies. An artificial data set with adjustable correlation is generated and applied to the computation, in addition to a real-world data set. The results show that SCAA performs well in a RMW environment with small order sizes, where orders typically contain only a single item of each product.