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dc.contributor.authorCabrerizo, F. J.en
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorAl-Hmouz, Ramien
dc.contributor.authorMorfeq, Alien
dc.contributor.authorSaeed Balamash, Abdullahen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.date.accessioned2015-10-19T08:39:31Z
dc.date.available2015-10-19T08:39:31Z
dc.date.issued2015-10
dc.identifier.citationCabrerizo, F. J. et al. (2015) Fuzzy decision making and consensus: challenges. Journal of Intelligent & Fuzzy Systems, 29 (3), pp. 1109-1118en
dc.identifier.urihttp://hdl.handle.net/2086/11277
dc.description.abstractGroup decision making is part of every organizational life. It is a type of participatory process in which multiple decision makers acting collectively, analyze problems, consider and evaluate several alternatives, and select from among the alternatives a solution. In such a situation, an important issue is the level of agreement or consensus achieved among the group of decision makers before obtaining the solution. In the beginning, consensus was meant as a full and unanimous agreement. Regrettably, this stringent concept of consensus in many cases is a utopia. As a result, and from a pragmatic point of view, it makes more sense to speak about a degree of consensus and, here, the theory of fuzzy sets has delivered new tools for the analysis of such imprecise phenomena like consensus. Given the significance of reaching an accepted solution by all the decision makers, consensus is a major aim of group decision making problems and, in such a way, it has obtained a great attention in the literature. However, there still exist several dares which have to be tackled by the researcheren
dc.language.isoen_USen
dc.publisherIOS Pressen
dc.subjectGroup decision makingen
dc.subjectconsensusen
dc.subjectfuzzy set theoryen
dc.subjectfuzzy logicen
dc.titleFuzzy decision making and consensus: challengesen
dc.typeArticleen
dc.identifier.doihttps://dx.doi.org/10.3233/IFS-151719
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderThis Project was funded by King Abdulaziz Univer- sity (KAU), under grant no. (27-135-35/HiCien
dc.projectidNAen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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