A new model and a hyper-heuristic approach for two-dimensional shelf space allocation

Bai, Ruibin; Van Woensel, Tom; Kendall, Graham; Burke, Edmund K.

Abstract

In this paper, we propose a two-dimensional shelf space allocation model. The second dimension stems from the height of the shelf. This results in an integer nonlinear programming model with a complex form of objective function. We propose a multiple neighborhood approach which is a hybridization of a simulated annealing algorithm with a hyper-heuristic learning mechanism. Experiments based on empirical data from both real-world and artificial instances show that the shelf space utilization and the resulting sales can be greatly improved when compared with a gradient method. Sensitivity analysis on the input parameters and the shelf space show the benefits of the proposed algorithm both in sales and in robustness.

Citation

Bai, R., Van Woensel, T., Kendall, G., & Burke, E. K. (in press). A new model and a hyper-heuristic approach for two-dimensional shelf space allocation. 4OR: A Quarterly Journal of Operations Research, 11(1), https://doi.org/10.1007/s10288-012-0211-2

• Journal Article Type: Article
• Acceptance Date: Aug 5, 2012
• Online Publication Date: Sep 29, 2012
• Deposit Date: Oct 25, 2017
• Publicly Available Date: Oct 25, 2017
• Journal: 4OR: A Quarterly Journal of Operations Research
• Print ISSN: 1619-4500
• Electronic ISSN: 1614-2411
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 1
• DOI: https://doi.org/10.1007/s10288-012-0211-2
• Keywords: Shelf space allocation; Two-dimensional; Retail; Multi-neighborhood search; Hyper-heuristics
• Public URL: https://nottingham-repository.worktribe.com/output/711177
• Publisher URL: https://doi.org/10.1007/s10288-012-0211-2
• Additional Information: The final publication is available at link.springer.com via http://dx.doi.org/10.1007/s10288-012-0211-2
• Contract Date: Oct 25, 2017