A consensus model for group decision making problems with linguistic interval fuzzy preference relations

► The consensus is a hot topic in the current research on fuzzy group decision making. ► We present a new consensus model to deal with group decision making problems in a new fuzzy linguistic context. ► We assume that the experts express their preferences by means of the linguistic interval fuzzy pr...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 39; no. 11; pp. 10022 - 10030
Main Authors:	Tapia Garcı´a, J.M., del Moral, M.J., Martínez, M.A., Herrera-Viedma, E.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01-09-2012
Subjects:	Consensus Criteria Decision making Expert systems Fuzzy Fuzzy logic Fuzzy set theory Group decision making Intervals Linguistic interval fuzzy preference relations Linguistics Group decision making Linguistic interval fuzzy preference relations Consensus
Online Access:	Get full text
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Summary:	► The consensus is a hot topic in the current research on fuzzy group decision making. ► We present a new consensus model to deal with group decision making problems in a new fuzzy linguistic context. ► We assume that the experts express their preferences by means of the linguistic interval fuzzy preference relations which is a new framework to develop consensus models. ► We provide a new consensus model that allows to automate the moderator’s actions in the consensus reaching processes in order to achieve a high agreement between the experts. Sometimes, we find decision situations in which it is difficult to express some preferences by means of concrete preference degrees. In this paper, we present a consensus model for group decision making problems in which the experts use linguistic interval fuzzy preference relations to represent their preferences. This model is based on two consensus criteria, a consensus measure and a proximity measure, and on the concept of coincidence among preferences. We compute both consensus criteria in the three representation levels of a preference relation and design an automatic feedback mechanism to guide experts in the consensus reaching process.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2
ISSN:	0957-4174 1873-6793
DOI:	10.1016/j.eswa.2012.02.008