A Model for Determining Retail Product Category Assortment and Shelf Space Allocation

TLDR

We develop a category‑management model that helps retailers decide which products to stock and how much shelf space to allocate to each. The model is a constrained optimization of assortment and shelf‑space allocation, solved by a simulated‑annealing heuristic that was tested on both a benchmark problem with a known optimum and a larger real‑world instance. The simulated‑annealing heuristic produced solutions comparable to the known optimum and outperformed a share‑of‑sales shelf‑allocation rule.

Abstract

We develop a category management model to aid retailers in the space constrained decisions of which products to stock (assortment) and how much shelf space to allocate to those products. The model is formulated as a constrained optimization problem with two basic decision variables: assortment and allocation of space to the items in the assortment. The non-linearities in the objective function and the zero-one decision variables disallow a closed form solution. We develop a heuristic solution procedure based on simulated annealing and test it on a problem with a known optimum. We also apply the technique to a larger problem without a known optimum. Finally, the solution found by simulated annealing is compared against a solution produced using a shelf allocation rule based on share of sales.