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dc.contributor.authordel Moral, Maria Joseen
dc.contributor.authorTapia Garcia, Juan Miguelen
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorAl-Hmouz, Aen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.date.accessioned2017-12-20T11:06:46Z
dc.date.available2017-12-20T11:06:46Z
dc.date.issued2018-04-19
dc.identifier.citationdel Moral, M. J., Tapia, J. M., Chiclana, F., Al-Hmouz, A., Herrera-Viedma, E (2017) An analysis of consensus approaches based on different concepts of coincidence. Journal of Intelligent and Fuzzy Systems, 34 (4), pp. 2247-2259en
dc.identifier.issn1064-1246
dc.identifier.issn1875-8967
dc.identifier.urihttp://hdl.handle.net/2086/15034
dc.descriptionThe file attached to this record is the author's final peer reviewed version.en
dc.description.abstractSoft consensus is a relevant topic in group decision making problems. Soft consensus measures are utilized to reflect the different agreement degrees between the experts leading the consensus reaching process. This may determine the final decision and the time needed to reach it. The concept of coincidence has led to two main approaches to calculating the soft consensus measures, namely, concordance among expert preferences and concordance among individual solutions. In the first approach the coincidence is obtained by evaluating the similarity among the expert preferences, while in the second one the concordance is derived from the measurement of the similarity among the solutions proposed by these experts. This paper performs a comparative study of consensus approaches based on both coincidence approaches. We obtain significant differences between both approaches by comparing several distance functions for measuring expert preferences and a consensus measure over the set of alternatives for measuring the solutions provided by experts. To do so, we use the nonparametric Wilcoxon signed-ranks test. Finally, these outcomes are analyzed using Friedman mean ranks in order to obtain a quantitative classification of the considered measurements according to the convergence criterion considered in the consensus reaching process.en
dc.language.isoen_USen
dc.publisherIOS Pressen
dc.subjectGroup decision makingen
dc.subjectfuzzy preference relationsen
dc.subjectconsensusen
dc.titleAn analysis of consensus approaches based on different concepts of coincidenceen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.3233/jifs-171282
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.explorer.multimediaNoen
dc.funderThe authors would like to acknowledge the FEDER financial support from the project TIN2016-75850-R.en
dc.projectidTIN2016-75850-Ren
dc.cclicenceCC-BY-NCen
dc.date.acceptance2017-12-08en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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