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dc.contributor.authorCao, Mingshuo
dc.contributor.authorChiclana Parrilla, Francisco 
dc.contributor.authorHerrera Viedma, Enrique 
dc.date.accessioned2021-10-22T07:10:10Z
dc.date.available2021-10-22T07:10:10Z
dc.date.issued2019-06
dc.identifier.citationPublished version: M. Cao... [et al.]. "A Personalized Consensus Feedback Mechanism Based on Maximum Harmony Degree," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 10, pp. 6134-6146, Oct. 2021, doi: [10.1109/TSMC.2019.2960052]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/71035
dc.descriptionThis work was sponsored by National Natural Science Foundation of China (NSFC) (No.71971135,71571166), EU project H2020-MSCA-IF-2016-DeciTrustNET-746398 and FEDER funds provided in the National Spanish project TIN2016-75850-R.es_ES
dc.description.abstractThis article proposes a framework of personalized feedback mechanism to help multiple inconsistent experts to reach consensus in group decision making by allowing to select different feedback parameters according to individual consensus degree. The general harmony degree (GHD) is defined to determine the before/after feedback difference between the original and revised opinions. It is proved that the GHD index is monotonically decreasing with respect to the feedback parameter, which means that higher parameters values will result in higher changes of opinions. An optimisation model is built with the GHD as the objective function and the consensus thresholds as constraints, with solution being personalized feedback advices to the inconsistent experts that keep a balance between consensus (group aim) and independence (individual aim). This approach is, therefore, more reasonable than the unpersonalized feedback mechanisms in which the inconsistent experts are forced to adopt feedback generated with only consensus target without considering the extent of the changes acceptable by individual experts. Furthermore, the following interesting theoretical results are also proved: (1) the personalized feedback mechanism guarantees that the increase of consensus level after feedback advices are implemented; (2) the GHD by the personalized feedback mechanism is higher than that of the unpersonalized one; and (3) the personalized feedback mechanism generalises the unpersonalized one as it is proved the latter is a particular type of the former. Finally, a numerical example is provided to model the feedback process and to corroborates these results when comparing both feedback mechanism approaches.es_ES
dc.description.sponsorshipNational Natural Science Foundation of China (NSFC) 71971135 71571166es_ES
dc.description.sponsorshipEuropean Commission H2020-MSCA-IF-2016-DeciTrustNET-746398 TIN2016-75850-Res_ES
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectGroup decision makinges_ES
dc.subjectConsensuses_ES
dc.subjectPersonalized feedback mechanismes_ES
dc.subjectHarmony degreees_ES
dc.titleA personalized consensus feedback mechanism based on maximum harmony degreees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/746398es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones_ES


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