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

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

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Authors

Ruibin Bai

Tom Van Woensel

Graham Kendall

Edmund K. Burke



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

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