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The Possible and the Necessary for Multiple Criteria Group Decision

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Algorithmic Decision Theory (ADT 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5783))

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Abstract

We introduce the principle of robust ordinal regression to group decision. We consider the main multiple criteria decision methods to which robust ordinal regression has been applied, i.e., UTAGMS and GRIP methods, dealing with choice and ranking problems, UTADISGMS, dealing with sorting (ordinal classification) problems, and ELECTREGMS, being an outranking method applying robust ordinal regression to well known ELECTRE methods. In this way, we obtain corresponding methods for group decision: UTAGMS-GROUP, UTADISGMS-GROUP and ELECTREGMS-GROUP.

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Author information

Authors and Affiliations

  1. Faculty of Economics, University of Catania, Italy

    Salvatore Greco

  2. Industrial Engineering Laboratory, Ecole Centrale Paris, France

    Vincent Mousseau

  3. Institute of Computing Science, Poznań University of Technology, Poznań, Poland

    Roman Słowiński

  4. Systems Research Institute, Polish Academy of Sciences, 00-441, Warsaw, Poland

    Roman Słowiński

Authors
  1. Salvatore Greco
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  2. Vincent Mousseau
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  3. Roman Słowiński
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Editor information

Editors and Affiliations

  1. Department of Pure and Applied Mathematics, University of Padova, Via Trieste 63, 35121, Padova, Italy

    Francesca Rossi

  2. LAMSADE-CNRS, University of Paris Dauphine, Place du Maréchal De Lattre de Tassigny, 75775, Paris Cedex 16, France

    Alexis Tsoukias

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© 2009 Springer-Verlag Berlin Heidelberg

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Greco, S., Mousseau, V., Słowiński, R. (2009). The Possible and the Necessary for Multiple Criteria Group Decision. In: Rossi, F., Tsoukias, A. (eds) Algorithmic Decision Theory. ADT 2009. Lecture Notes in Computer Science(), vol 5783. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04428-1_18

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  • DOI: https://doi.org/10.1007/978-3-642-04428-1_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04427-4

  • Online ISBN: 978-3-642-04428-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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