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A hierarchical ant based clustering algorithm and its use in three real-world applications

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  • Azzag, Hanene
  • Venturini, Gilles
  • Oliver, Antoine
  • Guinot, Christiane

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Suggested Citation

  • Azzag, Hanene & Venturini, Gilles & Oliver, Antoine & Guinot, Christiane, 2007. "A hierarchical ant based clustering algorithm and its use in three real-world applications," European Journal of Operational Research, Elsevier, vol. 179(3), pages 906-922, June.
  • Handle: RePEc:eee:ejores:v:179:y:2007:i:3:p:906-922
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    Cited by:

    1. Meisel, Stephan & Mattfeld, Dirk, 2010. "Synergies of Operations Research and Data Mining," European Journal of Operational Research, Elsevier, vol. 206(1), pages 1-10, October.
    2. Yannis Marinakis & Magdalene Marinaki & Michael Doumpos & Nikolaos Matsatsinis & Constantin Zopounidis, 2011. "A hybrid ACO-GRASP algorithm for clustering analysis," Annals of Operations Research, Springer, vol. 188(1), pages 343-358, August.
    3. Ruijiu Jin & Dongsheng Zuo & Xiangfeng Zhang & Wengang Sun, 2019. "An Orderly Power Utilization Scheme Based on an Intelligent Multi-Agent Apanage Management System," Energies, MDPI, vol. 12(23), pages 1-21, November.
    4. Jouan, Gabriel & Arnardottir, Erna Sif & Islind, Anna Sigridur & Óskarsdóttir, María, 2024. "An algorithmic approach to identification of gray areas: Analysis of sleep scoring expert ensemble non agreement areas using a multinomial mixture model," European Journal of Operational Research, Elsevier, vol. 317(2), pages 352-365.

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