A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout
- DOI
- 10.1080/18756891.2013.768447How to use a DOI?
- Keywords
- Store layout, Shelf location, Genetic algorithms, Tabu search, Association rule mining
- 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 commonly used by retailers are proposed. Finally, the effectiveness and applicability of the developed approaches are illustrated with numerical examples and a case study with data taken from a bookstore.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Tuncay Ozcan AU - Sakir Esnaf PY - 2013 DA - 2013/03/01 TI - A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout JO - International Journal of Computational Intelligence Systems SP - 261 EP - 278 VL - 6 IS - 2 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2013.768447 DO - 10.1080/18756891.2013.768447 ID - Ozcan2013 ER -