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Erratum: A hybrid genetic algorithmic approach to the maximally diverse grouping problem

Author

Listed:
  • Z P Fan

    (Northeastern University)

  • Y Chen

    (Shanghai University of Finance & Economics)

  • J Ma

    (City University of Hong Kong)

  • S Zeng

    (University of Arizona)

Abstract

Corrections to: Journal of the Operational Research Society (2010). doi: 10.1057/jors.2009.168 ; published online 6 January 2010 The maximally diverse grouping problem (MDGP) is a NP-complete problem. For such NP-complete problems, heuristics play a major role in searching for solutions. Most of the heuristics for MDGP focus on the equal group-size situation. In this paper, we develop a genetic algorithm (GA)-based hybrid heuristic to solve this problem considering not only the equal group-size situation but also the different group-size situation. The performance of the algorithm is compared with the established Lotfi–Cerveny–Weitz algorithm and the non-hybrid GA. Computational experience indicates that the proposed GA-based hybrid algorithm is a good tool for solving MDGP. Moreover, it can be easily modified to solve other equivalent problems.

Suggested Citation

  • Z P Fan & Y Chen & J Ma & S Zeng, 2011. "Erratum: A hybrid genetic algorithmic approach to the maximally diverse grouping problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1423-1430, July.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:7:d:10.1057_jors.2010.92
    DOI: 10.1057/jors.2010.92
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    References listed on IDEAS

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    Cited by:

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