Integrated storage assignment for an e-grocery fulfilment centre: Accounting for day-of-week demand patterns
David Winkelmann, Frederik Tolkmitt, Matthias Ulrich, Michael R\"omer

TL;DR
This paper presents an integrated MILP model for storage assignment in an e-grocery fulfilment centre, accounting for day-of-week demand patterns to improve efficiency and workload balance across days.
Contribution
It introduces a novel integrated approach for storage assignment that considers product selection, station, and shelf allocation simultaneously, including demand variability over the week.
Findings
Integrated approach outperforms sequential methods in efficiency.
Demand-aware storage assignment balances workload across days.
Model maintains high picking efficiency despite demand variation.
Abstract
In this paper, we deal with a storage assignment problem arising in a fulfilment centre of a major European e-grocery retailer. The centre can be characterised as a hybrid warehouse consisting of a highly efficient and partially automated fast-picking area designed as a pick-and-pass system with multiple stations, and a picker-to-parts area. The storage assignment problem considered in this paper comprises the decisions to select the products to be allocated to the fast-picking area, the assignment of the products to picking stations and the determination of a shelf within the assigned station. The objective is to achieve a high level of picking efficiency while respecting station workload balancing and precedence order constraints. We propose to solve this three-level problem using an integrated MILP model. In computational experiments with real-world data, we show that using the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Manufacturing and Logistics Optimization · Urban and Freight Transport Logistics · Consumer Retail Behavior Studies
