How to optimize storage classes in a unit-load warehouse

• Main Authors: ANG, Marcus, LIM, Yun Fong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Logistics; Unit-load warehouse; Storage-retrieval policy; Class-based storage; Business; Operations and Supply Chain Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/4541; https://ink.library.smu.edu.sg/context/lkcsb_research/article/5540/viewcontent/class.pdf
• Institution: Singapore Management University

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 crit- ical 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 prac- tice. 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 outper- forms 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.