The notion of consensus plays a key role in modelling group decisions, and for a long time it was meant as a strict and unanimous agreement, however, since various decision makers have different more or less conflicting opinions the traditional strict meaning of consensus is unrealistic. The human perception of consensus is much "softer", and people are willing to accept that a consensus has been reached when most or the more predominant actors agree on the preferences associated with the most relevant alternatives. The "soft" meaning of consensus, advocated as realistic and humanly consistent, can lead to solve in a more constructive way group decision making situations by using modelling tools based on fuzzy logic. In this paper we present a review of well known fuzzy logic-based approaches to model flexible consensus reaching dynamics, which constitute a well defined research area in the context of fuzzy GDM. First, the problem of modelling consensus under individual fuzzy preferences is considered, and two different models are synthesized. The first one is static and is based on the algebraic aggregation of the individual preferences aiming to find a consensus defined as the degree to which most of the important individuals agree as to their preferences concerning almost all of the relevant alternatives. The second one is dynamic and it combines a soft measure of collective disagreement with an inertial mechanism of opinion changing aversion. It acts on the network of single preference structures by a combination of a collective process of diffusion and an individual mechanism of inertia. Second, the use of Ordered Weighted Averaging (OWA) Operators to define a linguistic quantifier guided aggregation in the context of GDM is introduced and then generalized to the problem of Multi Expert Multi Criteria Decision Making for which a linguistic approach to define a consensus reaching strategy is presented. © 2008 Springer-Verlag Berlin Heidelberg.
Fedrizzi, M., Pasi, G. (2008). Fuzzy Approaches to Consensus Modelling in Group Decision Making. In D. Ruan, F. Hardeman, K. Van der Meer (a cura di), Intelligent Decision and Policy Making Support Systems (pp. 19-37). Springer [10.1007/978-3-540-78308-4_2].
Fuzzy Approaches to Consensus Modelling in Group Decision Making
PASI, GABRIELLA
2008
Abstract
The notion of consensus plays a key role in modelling group decisions, and for a long time it was meant as a strict and unanimous agreement, however, since various decision makers have different more or less conflicting opinions the traditional strict meaning of consensus is unrealistic. The human perception of consensus is much "softer", and people are willing to accept that a consensus has been reached when most or the more predominant actors agree on the preferences associated with the most relevant alternatives. The "soft" meaning of consensus, advocated as realistic and humanly consistent, can lead to solve in a more constructive way group decision making situations by using modelling tools based on fuzzy logic. In this paper we present a review of well known fuzzy logic-based approaches to model flexible consensus reaching dynamics, which constitute a well defined research area in the context of fuzzy GDM. First, the problem of modelling consensus under individual fuzzy preferences is considered, and two different models are synthesized. The first one is static and is based on the algebraic aggregation of the individual preferences aiming to find a consensus defined as the degree to which most of the important individuals agree as to their preferences concerning almost all of the relevant alternatives. The second one is dynamic and it combines a soft measure of collective disagreement with an inertial mechanism of opinion changing aversion. It acts on the network of single preference structures by a combination of a collective process of diffusion and an individual mechanism of inertia. Second, the use of Ordered Weighted Averaging (OWA) Operators to define a linguistic quantifier guided aggregation in the context of GDM is introduced and then generalized to the problem of Multi Expert Multi Criteria Decision Making for which a linguistic approach to define a consensus reaching strategy is presented. © 2008 Springer-Verlag Berlin Heidelberg.
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