Optimizing-Information-Granule-Based Consensus Reaching Model in Large-Scale Group Decision Making

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dc.contributor.authorLiang, Yingying
dc.contributor.authorPedrycz, Witold
dc.contributor.authorQin, Jindong
dc.date.accessioned2024-05-19T14:40:24Z
dc.date.available2024-05-19T14:40:24Z
dc.date.issued2024
dc.departmentİstinye Üniversitesien_US
dc.description.abstractIn large-scale group decision making (LSGDM), the consensus result is expected to be realized explicitly through reconciling various preferences provided by decision makers based on their personalized viewpoints. An information-granule-consensus-based decision brings about high flexibility and promising aspects in group decision making. The consensus reaching proposals reported so far paid little attention to the merits of granular computing for managing LSGDM problems. This article concerns an extension of the well-known analytic hierarchy process to the LSGDM scenario using the optimizing-information-granule-based consensus reaching method. The consensus measurement is first quantified using coverage and specificity to derive the optimal cluster using the fuzzy C-means algorithm. Then, based on the optimization model of an information granule leading from numerical to interval representation, a novel construction model of information granule from interval representations to type-2 interval representation is developed, which yields the consistency of the obtained result instead of proceeding with an extra revision. To achieve the desired consensus, a preference modification algorithm is designed to detect the adjusted decision maker and further provide adjustment suggestions following the reference decision maker. Finally, a numeric study illustrates the effectiveness and flexibility of the proposed method.en_US
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_US
dc.description.sponsorshipNo Statement Availableen_US
dc.identifier.doi10.1109/TFUZZ.2024.3353276
dc.identifier.endpage2427en_US
dc.identifier.issn1063-6706
dc.identifier.issn1941-0034
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85182933013en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2413en_US
dc.identifier.urihttps://doi.org10.1109/TFUZZ.2024.3353276
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4955
dc.identifier.volume32en_US
dc.identifier.wosWOS:001196731700012en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeee-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Transactions on Fuzzy Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectConsensus Reaching Modelen_US
dc.subjectLarge-Scale Group Decision Making (Lsgdm)en_US
dc.subjectMinimum Deviation Modelen_US
dc.subjectOptimizing Information Granuleen_US
dc.subjectType-2 Interval Representationen_US
dc.titleOptimizing-Information-Granule-Based Consensus Reaching Model in Large-Scale Group Decision Makingen_US
dc.typeArticleen_US

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