Efficient Material Flow and Storage Space Determination in Automated Distribution Centers

Abstract

There can be two automated storage and retrieval systems (AS/RS) in the same distribution center: one for pallets and the other for cases. Full pallets or half-full pallets are depalletized and moved to the case storage system. The number of cases depalletized daily for an item needs to be determined based on the average daily demand for that item. Too many depalletized cases ahead of time will inflate the required storage capacity of the case storage system. On the other hand, depalletizing only the necessary cases day by day might lead to too frequent material flow, and therefore more stacker cranes are necessary. Therefore, the number of depalletized pallets affects the number and utilization of stacker cranes in the pallet storage system. It also affects the needed space in the case storage system. This study determines the most efficient number of depalletized cases for three classes of items (A, B, and C), which are determined based on their daily demand. This is done using three scenarios. The total cost is minimized, considering the utilization of the two storage systems. More investigation was done for B items, which have daily demand levels of one layer of cases or more, but less than pallet size. First, analytical equations were formulated to model the system. The model was solved using a genetic algorithm (GA) with special chromosome representations. Results showed that B items can be grouped into two subgroups that are replenished based on two different material flow scenarios. Items with relatively large demand levels have scenario 3 as the optimal one. Results also showed that the model reduces both total costs and stacker crane utilization while improving system flexibility.