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dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorTapia García, Juan Miguelen
dc.contributor.authordel Moral, Maria Joseen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.date.accessioned2015-06-05T09:33:35Z
dc.date.available2015-06-05T09:33:35Z
dc.date.issued2015
dc.identifier.citationChiclana, F. (2015) Analyzing Consensus Measures in Group Decision Making. Procedia Computer Science (The third International Conference on Information Technology and Quantitative Management - ITQM 2015).en
dc.identifier.urihttp://hdl.handle.net/2086/11021
dc.description.abstractIn Group Decision Making (GDM) problems before to obtain a solution a high level of consensus among experts is required. Consensus measures are usually built using similarity functions measuring how close experts’ opinions or preferences are. Similarity functions are defined based on the use of a metric describing the distance between experts’ opinions or preferences. In the literature, different distance functions have been proposed to implement consensus measures. This paper presents analyzes the effect of the application of some different distance functions for measuring consensus in GDM. By using the nonparametric Wilcoxon matched-pairs signed-ranks test, it is concluded that different distance functions can produce significantly different results. Moreover, it is also shown that their application also has a significant effect on the speed of achieving consensus. Finally, these results are analysed and used to derive decision support rules, based on a convergent criterion, that can be used to control the convergence speed of the consensus process using the compared distance functions.en
dc.language.isoenen
dc.subjectGroup decision makingen
dc.subjectfuzzy preferencesen
dc.subjectsimilarityen
dc.subjectconsensusen
dc.subjectdecision support rulesen
dc.subjectWilcoxon testen
dc.titleAnalyzing Consensus Measures in Group Decision Makingen
dc.typeConferenceen
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderFEDERen
dc.funderAndalusian Excellence Projecten
dc.funderSpanish Ministry of Science and Innovationen
dc.projectidTIN2013-40658-Pen
dc.projectidTIC-05991en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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