Shelf space dimensioning and product allocation in retail stores

Retail shelves are adjustable by varying the number of shelf boards as well as the height and depth of each shelf board. Shelf planners adjust the boards accordingly at regular intervals when they create the shelf plans and allocate products. Current shelf planning models assume given shelf configurations and allocate only products. However, the dimensioning of a shelf segment and product allocation are interdependent. For instance, the height of one segment may be reduced if only small products are allocated or products cannot be stacked. This paper proposes the first integrated approach for shelf segment dimensioning and product allocation. It jointly determines the number of facings for each product, the shelf quantity and the size and number of shelf segments. We also identify and consider several restrictions for the shelf structure (e.g., technical options), allocation rules (e.g., maximum inventory reach) and allocation- and shelf-layout-dependent demand. We formulate the decision problem at hand which is an Integer Non-linear Program and apply a solution algorithm based on the application of bounds that are obtained by transferring constraints to a preprocessing stage. Doing so, we can reformulate the problem as Binary Integer Program, provide an exact approach and generate practical applicable and optimal solutions in a time-efficient manner. We show that integrating shelf dimensioning into product allocation results in up to 5% higher profits than benchmarks available in literature. By means of a case study we show how planning can be improved, and that the retailer's profit margin can be improved by up to 7%. (C) 2020 The Authors. Published by Elsevier B.V.