A Supply Chain Approach to Shelf Space Allocation

Abstract

The growing intensity of retail competition is forcing stores to strive for excellence in operations. In this environment, retailers have to balance the interconnected operations, such as transportation from warehouse, shelf space and backroom space allocations in a way that the overall profit is maximized. This study introduces an analytical model for optimally allocating shelf and backroom space among items with stochastic demands, and defining cycle time for each while considering transportation utilization between the warehouse and store. A constructive heuristic and Genetic Algorithm method are developed to solve the non-linear model. 72 different scenarios with 720 different problem instances are generated to compare heuristics and also to analyze the significance of several factors (shelf space, backroom space, truck cost, and problems size) on the results.