A new model and a hyper-heuristic approach for two-dimensional shelf space allocation
Bai, Ruibin; Van Woensel, Tom; Kendall, Graham; Burke, Edmund K.
Tom Van Woensel
Edmund K. Burke
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.
|Journal Article Type||Article|
|Journal||4OR: A Quarterly Journal of Operations Research|
|Peer Reviewed||Peer Reviewed|
|APA6 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), doi:10.1007/s10288-012-0211-2|
|Keywords||Shelf space allocation; Two-dimensional; Retail; Multi-neighborhood search; Hyper-heuristics|
|Copyright Statement||Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf|
|Additional Information||The final publication is available at link.springer.com via http://dx.doi.org/10.1007/s10288-012-0211-2|
A new model and a hyper-heuristic approach for two-dimensional shelf spa.._.pdf
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
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