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

R. Bai, T. Woensel, van, G. Kendall, E. Burke

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)
3 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)31-55
Number of pages25
Journal4OR : A Quarterly Journal of Operations Research
Volume11
Issue number1
DOIs
Publication statusPublished - 2013

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