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Maximizing single attribute diversity in group selection

Author

Listed:
  • Sergey Kovalev

    (25 rue de l’Université)

  • Isabelle Chalamon

    (25 rue de l’Université)

  • Fabio J. Petani

    (25 rue de l’Université)

Abstract

The studied problem consists in selecting a group of k entities out of n entities such that their diversity is maximized. Each entity is assumed to be characterized by a single numerical attribute. The diversity is measured by the total pairwise Euclidean or squared Euclidean distance. The problem appears in the formation of social or working groups. Under certain conditions, diversity is perceived as a positive factor influencing the group’s effectiveness. We propose simple $$O(n+k\log k)$$ O ( n + k log k ) time algorithms to solve this problem for both the total Euclidean and squared Euclidean distances.

Suggested Citation

  • Sergey Kovalev & Isabelle Chalamon & Fabio J. Petani, 2023. "Maximizing single attribute diversity in group selection," Annals of Operations Research, Springer, vol. 320(1), pages 535-540, January.
    • Handle: RePEc:spr:annopr:v:320:y:2023:i:1:d:10.1007_s10479-022-04764-7
    DOI: 10.1007/s10479-022-04764-7
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    References listed on IDEAS

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