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Consensus reaching via a GDSS with fuzzy majority and clustering of preference profiles

  • Section III Group Decision And Consensus Reaching Support
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Abstract

An interactive DSS for consensus reaching is presented. Experts provide their testimonies as fuzzy preference relations. The consensus reaching process is supervised by a moderator (“super-expert”). A degree of consensus, based on the concept of a fuzzy majority given as a linguistic quantifier is employed. Algorithms of cluster analysis are used to find groups of experts having similar preferences.

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Authors and Affiliations

  1. Department of Computer and Management Sciences, University of Trento, Via Inama 5, 38100, Trento, Italy

    M. Fedrizzi

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    J. Kacprzyk, J. W. Owsiński & S. Zadrożny

Authors
  1. M. Fedrizzi
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  2. J. Kacprzyk
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  3. J. W. Owsiński
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  4. S. Zadrożny
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Fedrizzi, M., Kacprzyk, J., Owsiński, J.W. et al. Consensus reaching via a GDSS with fuzzy majority and clustering of preference profiles. Ann Oper Res 51, 127–139 (1994). https://doi.org/10.1007/BF02032481

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