A Study of Different Protocols of Distribution of Information Granularity to Build Consensus in Fuzzy Group Decision-Making

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dc.contributor.authorGonzález-Quesada, Juan Carlos
dc.contributor.authorPérez, Ignacio Javier
dc.contributor.authorHerrera-Viedma, Enrique
dc.contributor.authorCabrerizo, Francisco
dc.date.accessioned2023-12-26T18:37:35Z
dc.date.available2023-12-26T18:37:35Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.221
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.otherd9b709fa-236e-4480-93b8-0e3208f5cd80
dc.identifier.urihttps://hdl.handle.net/10125/106599
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSoft Computing: Theory Innovations and Problem-Solving Benefits
dc.subjectconsensus
dc.subjectfuzzy preference relations
dc.subjectgroup decision-making
dc.subjectinformation granularity
dc.titleA Study of Different Protocols of Distribution of Information Granularity to Build Consensus in Fuzzy Group Decision-Making
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractInformation granularity has been regarded as a crucial design asset whose careful application becomes essential to create more realistic models. In processes of group decision-making, by admitting an average information granularity level, models can capture the diversity of knowledge sources, which allow them to be more reflective of reality. Concretely, a distribution of information granularity along with an optimization of the distribution process have been applied to build consensus while limiting the information loss. Given that there exist different protocols of distribution of information granularity, viz. a symmetric and uniform distribution, an asymmetric but uniform distribution, a symmetric but non-uniform distribution, and an asymmetric and non-uniform distribution, this study aims to discuss how we can take advantage of them to build consensus in group decision-making with fuzzy preference relations. Some numerical experiments are also conducted to analyze the performance and effectiveness of these protocols to build consensus.
dcterms.extent10 pages
prism.startingpage1754

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Soft Computing: Theory Innovations and Problem-Solving Benefits