A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout
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 comple...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2013-04-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/25868384.pdf |
| _version_ | 1811300882747228160 |
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| author | Tuncay Ozcan Sakir Esnaf |
| author_facet | Tuncay Ozcan Sakir Esnaf |
| author_sort | Tuncay Ozcan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T06:59:01Z |
| format | Article |
| id | doaj.art-93916c7a57984c47946fc2bbab3e2c2f |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-04-13T06:59:01Z |
| publishDate | 2013-04-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-93916c7a57984c47946fc2bbab3e2c2f2022-12-22T02:57:10ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832013-04-016210.1080/18756891.2013.768447A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore LayoutTuncay OzcanSakir EsnafIn 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.https://www.atlantis-press.com/article/25868384.pdfStore layoutShelf locationGenetic algorithmsTabu searchAssociation rule mining |
| spellingShingle | Tuncay Ozcan Sakir Esnaf A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout International Journal of Computational Intelligence Systems Store layout Shelf location Genetic algorithms Tabu search Association rule mining |
| title | A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout |
| title_full | A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout |
| title_fullStr | A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout |
| title_full_unstemmed | A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout |
| title_short | A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout |
| title_sort | discrete constrained optimization using genetic algorithms for a bookstore layout |
| topic | Store layout Shelf location Genetic algorithms Tabu search Association rule mining |
| url | https://www.atlantis-press.com/article/25868384.pdf |
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