Optimizing Storage Assignment Under Time-Varying Demand and Supply
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Abstract
Putaway and order picking are high-cost warehousing activities, accounting for up to 55 % of the total cost in the warehouse. Furthermore, most of the time is being wasted on trips to store and pick up, which can add up to 55 % of the total working time. This research proposed mathematical models to determine the optimal storage locations in each period by minimizing pick up and storage traveling distances under two storage policies, including dedicated storage and random storage. The efficiency in minimizing traveling distance was studied and compared by applying the mathematical model with Add-in Open Solver in Microsoft Excel using Gurobi Optimizer solver engine to solve the problem. Under the assumption that the warehouse knew the change in demand and supply in advance, the results indicated that the random storage policy was more efficient in minimizing traveling distance than the dedicated storage policy. In fact, the total traveling distance of the random storage policy was 11.2 % less than the dedicated storage policy.
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