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A Population-Based Algorithm for Learning a Majority Rule Sorting Model with Coalitional Veto

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Evolutionary Multi-Criterion Optimization (EMO 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10173))

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Abstract

MR-Sort (Majority Rule Sorting) is a multiple criteria sorting method which assigns an alternative a to category \(C^h\) when a is better than the lower limit of \(C^h\) on a weighted majority of criteria, and this is not true with the upper limit of \(C^h\). We enrich the descriptive ability of MR-Sort by the addition of coalitional vetoes which operate in a symmetric way as compared to the MR-Sort rule w.r.t. to category limits, using specific veto profiles and veto weights. We describe a heuristic algorithm to learn such an MR-Sort model enriched with coalitional veto from a set of assignment examples, and show how it performs on real datasets.

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Notes

  1. 1.

    It is worth noting that outranking methods used for sorting are not subject to Condorcet effects (cycles in the preference relation), since alternatives are not compared in pairwise manner but only to profiles limiting the categories.

  2. 2.

    “weak preference” means being “at least as good as”.

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Authors and Affiliations

  1. CentraleSupelec, Université Paris-Saclay, Grande Voie des Vignes, 92295, Châtenay Malabry, France

    Olivier Sobrie & Vincent Mousseau

  2. Université de Mons, Faculté Polytechnique, 9, Rue de Houdain, 7000, Mons, Belgium

    Olivier Sobrie & Marc Pirlot

Authors
  1. Olivier Sobrie
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  2. Vincent Mousseau
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  3. Marc Pirlot
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Corresponding authors

Correspondence to Olivier Sobrie , Vincent Mousseau or Marc Pirlot .

Editor information

Editors and Affiliations

  1. University of Münster, Münster, Germany

    Heike Trautmann

  2. TU Dortmund University, Dortmund, Germany

    Günter Rudolph

  3. University of Wuppertal, Wuppertal, Germany

    Kathrin Klamroth

  4. CINVESTAV-IPN, Mexico City, Mexico

    Oliver Schütze

  5. Clemson University, Clemson, South Carolina, USA

    Margaret Wiecek

  6. University of Surrey, Guildford, United Kingdom

    Yaochu Jin

  7. University of Münster, Münster, Germany

    Christian Grimme

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Sobrie, O., Mousseau, V., Pirlot, M. (2017). A Population-Based Algorithm for Learning a Majority Rule Sorting Model with Coalitional Veto. In: Trautmann, H., et al. Evolutionary Multi-Criterion Optimization. EMO 2017. Lecture Notes in Computer Science(), vol 10173. Springer, Cham. https://doi.org/10.1007/978-3-319-54157-0_39

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  • DOI: https://doi.org/10.1007/978-3-319-54157-0_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54156-3

  • Online ISBN: 978-3-319-54157-0

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