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dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorTapia García, J. M.en
dc.contributor.authordel Moral, Maria Joseen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.date.accessioned2013-01-02T10:27:29Z
dc.date.available2013-01-02T10:27:29Z
dc.date.issued2013-02
dc.identifier.citationChiclana, F., Tapia-Garcia, J.M., del Moral, M.J. and Herrera-Viedma, E. (2013) A Statistical Comparative Study of Different Similarity Measures of Consensus in Group Decision Making. Information Sciences, 221, pp. 110-123en
dc.identifier.urihttp://hdl.handle.net/2086/7972
dc.descriptionResearch conducted in collaboration between DMU and University of Granada (Spain). DIGITS, Department of Informatics, Faculty of Technology, De Montfort University, Leicester LE1 9BH, UK; Department of Quantitative Methods in Economic and Business, University of Granada, 18071 Granada, Spain; Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain; Department of Computer Science and A.I., University of Granada, 18071 Granada, Spainen
dc.descriptionNOTICE: this is the author’s version of a work that was accepted for publication in <Journal title>. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Sciences. http://dx.doi.org/10.1016/j.ins.2012.09.014
dc.description.abstractAn essential aim in group decision making (GDM) problems is to achieve a high level of consensus among experts. Consensus is defined as general or widespread agreement, and it is usually modelled mathematically via a similarity function 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 metrics or distance functions have been proposed to implement in consensus models, but no study has been carried out to analyse the influence the use of different distance functions can have in the GDM process. This paper presents a comparative study of 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.description.sponsorshipThe authors would like to acknowledge FEDER financial support from the Project FUZZYLING-II Project TIN2010-17876; the financial support from the Andalusian Excellence Projects TIC-05299 and TIC-05991, and also from the research Project MTM2009-08886. Prof. Francisco Chiclana would like to acknowledge the financial support from the University of Granada 2012 GENIL Strengthening through Short-Visits research program (Ref. GENIL-SSV).en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectGroup decision makingen
dc.subjectFuzzy preferencesen
dc.subjectSimilarityen
dc.subjectConsensusen
dc.subjectDecision support rulesen
dc.subjectWilcoxon testen
dc.titleA Statistical Comparative Study of Different Similarity Measures of Consensus in Group Decision Makingen
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1016/j.ins.2012.09.014
dc.researchgroupDIGITSen
dc.peerreviewedYesen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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