Publication Date

2019

Document Type

Thesis

Committee Members

Pratik Parikh, Ph.D. (Advisor); Kunal Swani, Ph.D. (Committee Member); Corinne Mowrey, Ph.D. (Committee Member)

Degree Name

Master of Science in Industrial and Human Factors Engineering (MSIHE)

Abstract

The physical design of a retail store is known to influence the attitude and behavior of shoppers, in turn affecting the store’s performance. While literature in retail design has alluded to the impact of changes in department placements on impulse revenue, it has not accounted for the changes in the path of a shopper due to such modifications. Shopper path changes can alter a department’s visibility to the shoppers as they pass by, and such visibility eventually impacts that department’s impulse revenue. To address this gap, we study the retail facility layout problem by accounting for changes in the shopper path and door placement; we refer to it as RFLP-SPDP. We propose an optimization model for RFLP-SPDP that optimally places departments in the store in order to maximize the expected per shopper impulse revenue for the retailer. Because the dependency of shopper path changes on with changing layouts could not be expressed in a closed analytical form, we propose a Simulated Annealing based shortest path heuristic. This is then embedded in a Particle Swarm Optimization based solution approach to solve the overall RFLP-SPDP and implemented using parallel processing. Our experiments indicate that the derived solutions are sensitive to the shopper basket size, the shape of the store, and the number of doors and their location. Our results suggest up to 13.71% increase in impulse revenue for a deeper store over a square-shaped store, while up to 9.65% increase in a one side-door store over other door combinations. We illustrate the use of our proposed approach using the layout of a leading US retailer’s store.

Page Count

54

Department or Program

Department of Biomedical, Industrial and Human Factors Engineering

Year Degree Awarded

2019


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