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Metaheuristics: Progress as Real Problem Solvers pp 87–108Cite as

An Investigation of Automated Planograms Using a Simulated Annealing Based Hyper-Heuristic

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Part of the book series: Operations Research/Computer Science Interfaces Series ((ORCS,volume 32))

Abstract

This paper formulates the shelf space allocation problem as a non-linear function of the product net profit and store-inventory. We show that this model is an extension of multi-knapsack problem, which is itself an NP-hard problem. A two-stage relaxation is carried out to get an upper bound of the model. A simulated annealing based hyper-heuristic algorithm is proposed to solve several problem instances with different problem sizes and space ratios. The results show that the simulated annealing hyper-heuristic significantly outperforms two conventional simulated annealing algorithms and other hyper-heuristics for all problem instances. The experimental results show that our approach is a robust and efficient approach for the shelf space allocation problem.

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Author information

Authors and Affiliations

  1. Automated Scheduling, Optimisation and Planning (ASAP) Research Group, School of Computer Science & IT, University of Nottingham, Nottingham, NG8 IBB, UK

    Ruibin Bai & Graham Kendall

Authors
  1. Ruibin Bai
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  2. Graham Kendall
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Editor information

Editors and Affiliations

  1. Kyoto University, Japan

    Toshihide Ibaraki , Koji Nonobe  & Mutsunori Yagiura ,  & 

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© 2005 Springer Science+Business Media, Inc.

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Bai, R., Kendall, G. (2005). An Investigation of Automated Planograms Using a Simulated Annealing Based Hyper-Heuristic. In: Ibaraki, T., Nonobe, K., Yagiura, M. (eds) Metaheuristics: Progress as Real Problem Solvers. Operations Research/Computer Science Interfaces Series, vol 32. Springer, Boston, MA. https://doi.org/10.1007/0-387-25383-1_4

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