Case study · Warehouse optimization
Small changes.Better picking.
Improve an existing warehouse, one informed rearrangement at a time.
A beverage warehouse case study shows how order data and mathematical optimization can identify which products to move, where to place them, and when to review the arrangement.
01 / The challenge
Improve placement without starting over.
Products frequently ordered together can be spread across several aisles, increasing the effort of picking each order. Yet rearranging a warehouse also takes work: stock must be moved, labels and systems updated, and picking teams must adapt. The challenge is to identify changes worth making.
02 / The approach
Connect order patterns with operational constraints.
The model groups products that are often ordered together to reduce aisle visits. It also considers replenishment needs, available capacity, and placement restrictions that preserve the required picking sequence. A limit on the number of products moved lets planners evaluate selective changes to the existing arrangement.
03 / The validation
Test assignments against later orders.
The study used 356,451 orders from August 2017 to August 2019. Assignments calculated from the first year's orders were evaluated against the second year. Further analyses examined how changing demand affects performance and how much improvement can be achieved by moving only a small part of the assortment.
Study findings
Targeted moves. Regular reviews.
improvement in the model's objective when the assignment was recalculated using the second year's orders.
Moving just 30 products (2.6% of the assortment) captured 22.5% of the improvement available in the study's rearrangement comparison.
Results from computational evaluation of historical orders, not measured reductions in operating costs. The findings support reviewing storage assignments regularly and prioritizing a manageable set of changes.
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