Abstract
Abstract In retail industry, one of the most important decisions of shelf space management is the shelf location decision for products and product categories to be displayed in-store. The shelf location that products are displayed has a significant impact on product sales. At the same time, displaying complementary products close to each other increases the possibility of cross-selling of products. In this study, firstly, for a bookstore retailer, a mathematical model is developed based on association rule mining for store layout problem which includes the determination of the position of products and product categories which are displayed in-store shelves. Then, because of the NP-hard nature of the developed model, an original heuristic approach is developed based on genetic algorithms for solving large-scale real-life problems. In order to compare the performance of the genetic algorithm based heuristic with other methods, another heuristic approach based on tabu search and a simple heuristic that is co...
Highlights
Location is an important factor affecting product demand in retail shelf space management
In order to compare the performance of the genetic algorithm based heuristic with other methods, another heuristic approach based on tabu search and a simple rule that is commonly used by retailers are proposed
In order to compare the performance of the genetic algorithm based heuristic with other methods, another heuristic approach based on tabu search is proposed
Summary
Location is an important factor affecting product demand in retail shelf space management. In another study related to the location effect in retail stores, Chen et al. investigated the relationship between spatial distances of the products displayed and their sales and analyzed the impact of the proximity of the shelf space on sales For this purpose, a powerful algorithm based on association rule mining was developed. Hwang et al. dealt with the shelf space allocation problem, in which the rate of demand is a function of the inventory level displayed and the location of the shelf; and presented two different approaches, based on the gradient search and genetic algorithm, as the solution for the developed model. In the few studies related to retail store layout, Botsali and Peters developed a network based layout design and Yapicioglu and Smith used a racetrack layout Models proposed in these studies do not satisfy the specificities and constraints of a bookstore layout. A modified genetic algorithm based approach which is differentiated by the generation of the initial solution and crossover and mutation operators from classical genetic algorithm, is designed for solving this model
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