CONSENSUS MODELLING IN GROUP DECISION MAKING: DYNAMICAL APPROACH BASED ON FUZZY PREFERENCES

Mario Fedrizzi (), Michele Fedrizzi and R. A. Marques Pereira
Additional contact information
Mario Fedrizzi: Dipartimento di Informatica e Studi Aziendali DISA, Università di Trento, Via Inama 5, 38100 Trento, Italy
Michele Fedrizzi: Dipartimento di Informatica e Studi Aziendali DISA, Università di Trento, Via Inama 5, 38100 Trento, Italy
R. A. Marques Pereira: Dipartimento di Informatica e Studi Aziendali DISA, Università di Trento, Via Inama 5, 38100 Trento, Italy

New Mathematics and Natural Computation (NMNC), 2007, vol. 03, issue 02, 219-237

Abstract: The. notion of consensus plays an important role in group decision making, particularly when the collective preference structure is generated by a dynamical aggregation process of the single individual preference structures. In this dynamical process of aggregation each single decision maker gradually transforms his/her preference structure by combining it, through iterative weighted averaging, with the preference structures of the remaining decision makers. In this way, the collective decision emerges dynamically as a result of the consensual interaction among the various decision makers in the group. From the point of view of applied mathematics, the models of consensual dynamics stand in the context of multi-agent complex systems, with interactive and nonlinear dynamics. The consensual interaction among the various agents (decision makers) acts on their state variables (the preferences) in order to optimize an appropriate measure of consensus, which can be of type 'hard' (unanimous agreement within the group of decision makers) or 'soft' (partial agreement within the group of decision makers). In this paper, we study the modelling of consensus reaching when the individual testimonies are assumed to be expressed as fuzzy preference relations. Here consensus is meant as the degree to which most of the experts agree on the preferences associated to the most relevant alternatives. First of all we derive a degree of dissensus based on linguistic quantifiers and then we introduce a form of network dynamics in which the quantifiers are represented by scaling functions. Finally, assuming that the decision makers can express their preferences in a more flexible way, i.e. by using triangular fuzzy numbers, we describe the iterative process of opinion transformation towards consensus via the gradient dynamics of a cost function expressed as a linear combination of a dissensus cost function and an inertial cost function.

Keywords: Group decision making; consensus reaching; fuzzy preference relations; linguistic quantifiers; fuzzy numbers; gradient dynamics (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S1793005707000744
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:nmncxx:v:03:y:2007:i:02:n:s1793005707000744

Ordering information: This journal article can be ordered from

DOI: 10.1142/S1793005707000744

Access Statistics for this article

New Mathematics and Natural Computation (NMNC) is currently edited by Paul P Wang

More articles in New Mathematics and Natural Computation (NMNC) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().