Greedy Policies for Storage Location Management in Distribution Centers

Digital transformation (DX) has a significant impact on the supply chain, and this could promote the utilization of data and digital technologies in all systems. In this study, a storage location assignment problem was investigated utilizing a DX method to improve the efficiency of picking operations in distribution centers by focusing on the schedules of stored items. Storage assignment policies utilizing the arrival and shipping information of items to determine the optimal or near-optimal storage allocations to shorten the travel distance were considered. First, it was assumed that all arrival and shipping dates of items in the planning horizon are known. Then, greedy policies focusing on arrival dates, shipping dates, and the storage durations of items were compared. The greedy policy based on shipping dates showed the highest performance. Next, the ways in which these properties can be utilized to obtain the optimal solution efficiently were investigated. Finally, under the assumption that information on the arrival and shipping dates of all items is incomplete, policies to improve the greedy policy using arrival dates were considered.