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Heuristic and meta-heuristic approaches for multi-period shelf-space optimization: the case of motion picture retailing


  • S Raut

    (Tata Consultancy Services Limited)

  • S Swami

    () (DEI (Deemed University))

  • M P Moholkar

    (GAD Group, IBM Global Services)


Abstract The retail industry is in a highly competitive situation currently. The success of the industry depends upon the efficient allocation of products in the shelf space. Several previous authors have developed mathematical models for optimal shelf-space allocation. We extend the prior research in the direction of the multi-period problem and introduce more realistic characteristics, such as product demand perishability, pricing contract and cross-elasticity. The new characteristics help us address the case of the real-life movie allocation problem in multiplexes. We formulate a linear integer programming model to represent the problem. The proposed model shows a potential benefit of at least 11% increase in revenue for a multiplex theatre situation as compared to the existing methods. We also propose two greedy heuristics and a genetic algorithm to solve the same problem. A computational study shows that the genetic algorithm performs better than the existing method.

Suggested Citation

  • S Raut & S Swami & M P Moholkar, 2009. "Heuristic and meta-heuristic approaches for multi-period shelf-space optimization: the case of motion picture retailing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1335-1348, October.
  • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:10:d:10.1057_jors.2008.98
    DOI: 10.1057/jors.2008.98

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    References listed on IDEAS

    1. Marcel Corstjens & Peter Doyle, 1981. "A Model for Optimizing Retail Space Allocations," Management Science, INFORMS, vol. 27(7), pages 822-833, July.
    2. Yang, Ming-Hsien & Chen, Wen-Cher, 1999. "A study on shelf space allocation and management," International Journal of Production Economics, Elsevier, vol. 60(1), pages 309-317, April.
    3. Willy Gochet & Yves Smeers, 1979. "A Branch-and-Bound Method for Reversed Geometric Programming," Operations Research, INFORMS, vol. 27(5), pages 982-996, October.
    4. Sanjeev Swami & Jehoshua Eliashberg & Charles B. Weinberg, 1999. "SilverScreener: A Modeling Approach to Movie Screens Management," Marketing Science, INFORMS, vol. 18(3), pages 352-372.
    5. Yang, Ming-Hsien, 2001. "An efficient algorithm to allocate shelf space," European Journal of Operational Research, Elsevier, vol. 131(1), pages 107-118, May.
    6. Andrew Lim & Brian Rodrigues & Xingwen Zhang, 2004. "Metaheuristics with Local Search Techniques for Retail Shelf-Space Optimization," Management Science, INFORMS, vol. 50(1), pages 117-131, January.
    7. Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
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    Cited by:

    1. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.


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