How to optimize storage classes in a unit-load warehouse

We study a problem of optimizing storage classes in a unit-load warehouse such that the total travel cost is minimized. This is crucial to the operational efficiency of unit-load warehouses, which constitute a critical part of a supply chain. We propose a novel approach called the FB method to solve the problem. The FB method is suitable for general receiving-dock and shipping-dock locations that may not coincide. The FB method first ranks the locations according to the frequencies that they are visited, which are estimated by a linear program based on the warehouse's layout as well as the products' arrivals and demands. The method then sequentially groups the locations into a number of classes that is implementable in practice. After forming the classes, we use a policy based on robust optimization to determine the storage and retrieval decisions. We compare the robust policy with the traditional storage-retrieval policies on their respective optimized classes. Our results suggest that if the warehouse utilization is low, different class-formation methods may lead to very different total travel costs, with our approach being the most efficient. We observe the robustness of this result across various parameter settings. A case study based on data from a third-party logistics provider suggests that the robust policy under the FB method outperforms the other storage-retrieval policies by at least 8% on average, which indicates the potential savings by our approach in practice. One of our findings is that the importance of optimizing classes depends on the warehouse utilization. (C) 2019 Elsevier B.V. All rights reserved.