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4OR

, Volume 11, Issue 1, pp 31–55 | Cite as

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

  • Ruibin Bai
  • Tom van Woensel
  • Graham Kendall
  • Edmund K. Burke
Research Paper

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.

Keywords

Shelf space allocation Two-dimensional Retail   Multi-neighborhood search Hyper-heuristics 

MSC classification

90B80 Discrete Location and Assignment 

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Ruibin Bai
    • 1
  • Tom van Woensel
    • 2
  • Graham Kendall
    • 3
    • 4
  • Edmund K. Burke
    • 5
  1. 1.Department of Computer ScienceUniversity of Nottingham Ningbo ChinaNingboChina
  2. 2.School of Industrial EngineeringTechnische Universiteit EindhovenEindhovenThe Netherlands
  3. 3.School of Computer ScienceUniversity of NottinghamNottinghamUK
  4. 4.School of Computer ScienceUniversity of NottinghamSemenyihMalaysia
  5. 5.Department of Computing Science and MathematicsUniversity of StirlingStirlingUK

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