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The Dynamics of Consensus in Group Decision Making: Investigating the Pairwise Interactions between Fuzzy Preferences

  • Chapter
Preferences and Decisions

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 257))

Abstract

In this paper we present an overviewof the soft consensusmodel in group decision making and we investigate the dynamical patterns generated by the fundamental pairwise preference interactions on which the model is based.

The dynamical mechanism of the soft consensus model is driven by the minimization of a cost function combining a collective measure of dissensus with an individual mechanism of opinion changing aversion. The dissensus measure plays a key role in the model and induces a network of pairwise interactions between the individual preferences.

The structure of fuzzy relations is present at both the individual and the collective levels of description of the soft consensusmodel: pairwise preference intensities between alternatives at the individual level, and pairwise interaction coefficients between decision makers at the collective level.

The collective measure of dissensus is based on non linear scaling functions of the linguistic quantifier type and expresses the degree to which most of the decision makers disagree with respect to their preferences regarding the most relevant alternatives. The graded notion of consensus underlying the dissensus measure is central to the dynamical unfolding of the model.

The original formulation of the soft consensus model in terms of standard numerical preferences has been recently extended in order to allow decision makers to express their preferences by means of triangular fuzzy numbers. An appropriate notion of distance between triangular fuzzy numbers has been chosen for the construction of the collective dissensus measure.

In the extended formulation of the soft consensus model the extra degrees of freedom associated with the triangular fuzzy preferences, combined with non linear nature of the pairwise preference interactions, generate various interesting and suggestive dynamical patterns. In the present paper we investigate these dynamical patterns which are illustrated by means of a number of computer simulations.

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Authors and Affiliations

  1. Department of Computer and Management Science, University of Trento, via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi, Michele Fedrizzi, R. A. Marques Pereira & Matteo Brunelli

  2. IAMSR, Turku Centre for Computer Science, Abo Akademi University, Joukahainengatan 3-5A, FIN-20520, Abo, Finland

    Matteo Brunelli

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  1. Mario Fedrizzi
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  2. Michele Fedrizzi
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  3. R. A. Marques Pereira
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  4. Matteo Brunelli
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Editors and Affiliations

  1. Department of Economics and Quantitative Methods, University of Catania, Corso Italia 55, 95129, Catania, Italy

    Salvatore Greco

  2. Department of Computer and Management Sciences, University of Trento, Via Inama 5, 38122, Trento, Italy

    Ricardo Alberto Marques Pereira

  3. Department of Economical and Social Sciences, University of Sannio at Benevento, Via delle Puglie, 82100, Benevento, Italy

    Massimo Squillante

  4. Machine Intelligence Institute, Iona College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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

    Janusz Kacprzyk

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Fedrizzi, M., Fedrizzi, M., Pereira, R.A.M., Brunelli, M. (2010). The Dynamics of Consensus in Group Decision Making: Investigating the Pairwise Interactions between Fuzzy Preferences. In: Greco, S., Marques Pereira, R.A., Squillante, M., Yager, R.R., Kacprzyk, J. (eds) Preferences and Decisions. Studies in Fuzziness and Soft Computing, vol 257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15976-3_10

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