Retail Store Layout Optimization for Maximum Product Visibility

TL;DR

This paper presents a hierarchical optimization methodology for retail store layout design that maximizes product visibility, using a linearized model of a complex quadratic assignment problem, demonstrated with real-world data.

Contribution

It introduces a novel hierarchical optimization approach for store layout planning that effectively captures shopper behavior and improves product visibility using linearized quadratic assignment models.

Findings

Linearized models significantly improve store layouts.

Method effectively captures shopper paths and eligibility constraints.

Demonstrated with real-world numerical example.

Abstract

It is well-established that increased product visibility to shoppers leads to higher sales for retailers. In this study, we propose an optimization methodology which assigns product categories and subcategories to store locations and sublocations to maximize the overall visibility of products to shoppers. The methodology is hierarchically developed to meet strategic and tactical layout planning needs of brick-and-mortar retailers. Layouts in both levels of planning are optimized considering eligibility requirements and complete set of shopper paths, thus, they successfully capture the unique shopping behavior of consumers in a store's region. The resulting mathematical optimization problem is recognized as a special instance of the well-known Quadratic Assignment Problem, which is considered computationally as one of the hardest optimization problems. We adopt a linearization technique and demonstrate via a real-world numerical example that our linearized optimization models substantially improve the store layout, hence, can be used in practical applications as a vital decision support model for store layout planning.