2022/03/24 by Maximilian Schiffer, Nils Boysen, Patrick S. Klein +2 · 53 citations
Engineering · Mathematics · #Advanced Manufacturing and Logistics Optimization #Business #Computer science #Database #Engineering #Industrial engineering #Marketing #Mathematics #Operations research #Optimization and Packing Problems #Order picking #Routing (electronic design automation) #Stock (firearms) #Urban and Freight Transport Logistics #Warehouse
paper · open access · doi:10.1287/mnsc.2021.4275
published in Management Science 68(10), 7497-7517 (Institute for Operations Research and the Management Sciences)
openalex publication_date 2022/03/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
In e-commerce warehouses, online retailers increase their efficiency by using a mixed-shelves (or scattered storage) concept, where unit loads are purposefully broken down into single items, which are individually stored in multiple locations. Irrespective of the stock keeping units a customer jointly orders, this storage strategy increases the likelihood that somewhere in the warehouse the items of the requested stock keeping units will be in close vicinity, which may significantly reduce an order picker’s unproductive walking time. This paper optimizes picker routing through such mixed-shelves warehouses. Specifically, we introduce a generic exact algorithmic framework that covers a multitude of picking policies, independently of the underlying picking zone layout, and is suitable for real-time applications. This framework embeds a bidirectional layered graph algorithm that provides the best known performance for the simple picking problem with a single depot and no further attributes. We compare three different real-world e-commerce warehouse settings that differ slightly in their application of scattered storage and in their picking policies. Based on these, we derive additional layouts and settings that yield further managerial insights. Our results reveal that the right combination of drop-off points, dynamic batching, the utilization of picking carts, and the picking zone layout can greatly improve the picking performance. In particular, some combinations of policies yield efficiency increases of more than 30% compared with standard policies currently used in practice. This paper was accepted by Chung Piaw Teo, optimization.