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Scatter tabu search for multiobjective clustering problems

Author

Listed:
  • R Caballero

    (University of Málaga)

  • M Laguna

    (University of Colorado)

  • R Martí

    (University of Valencia)

  • J Molina

    (University of Málaga)

Abstract

We propose a hybrid heuristic procedure based on scatter search and tabu search for the problem of clustering objects to optimize multiple criteria. Our goal is to search for good approximations of the efficient frontier for this class of problems and provide a means for improving decision making in multiple application areas. Our procedure can be viewed as an extension of SSPMO (a scatter search application to nonlinear multiobjective optimization) to which we add new elements and strategies specially suited for combinatorial optimization problems. Clustering problems have been the subject of numerous studies; however, most of the work has focused on single-objective problems. Clustering using multiple criteria and/or multiple data sources has received limited attention in the operational research literature. Our scatter tabu search implementation is general and tackles several problems classes within this area of combinatorial data analysis. We conduct extensive experimentation to show that our method is capable of delivering good approximations of the efficient frontier for improved analysis and decision making.

Suggested Citation

  • R Caballero & M Laguna & R Martí & J Molina, 2011. "Scatter tabu search for multiobjective clustering problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(11), pages 2034-2046, November.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:11:d:10.1057_jors.2010.180
    DOI: 10.1057/jors.2010.180
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    References listed on IDEAS

    as
    1. Julian Molina & Manuel Laguna & Rafael Martí & Rafael Caballero, 2007. "SSPMO: A Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization," INFORMS Journal on Computing, INFORMS, vol. 19(1), pages 91-100, February.
    2. P. Hansen & B. Jaumard & O. Frank, 1989. "Maximum sum-of-splits clustering," Journal of Classification, Springer;The Classification Society, vol. 6(1), pages 177-193, December.
    3. R. Baños & C. Gil & J. Reca & J. Martínez, 2009. "Implementation of scatter search for multi-objective optimization: a comparative study," Computational Optimization and Applications, Springer, vol. 42(3), pages 421-441, April.
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    Cited by:

    1. Barat, Somjit & Amos, Clinton & Paswan, Audhesh & Holmes, Gary, 2013. "An exploratory investigation into how socioeconomic attributes influence coupons redeeming intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 20(2), pages 240-247.
    2. A. D. López-Sánchez & J. Sánchez-Oro & M. Laguna, 2021. "A New Scatter Search Design for Multiobjective Combinatorial Optimization with an Application to Facility Location," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 629-642, May.
    3. Huerta-Muñoz, Diana L. & Ríos-Mercado, Roger Z. & Ruiz, Rubén, 2017. "An iterated greedy heuristic for a market segmentation problem with multiple attributes," European Journal of Operational Research, Elsevier, vol. 261(1), pages 75-87.

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