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dc.contributor.authorLiu, Xiu
dc.contributor.authorXu, Yejun
dc.contributor.authorMontes Soldado, Rosa Ana 
dc.contributor.authorDing, Ru-Xi
dc.contributor.authorHerrera Triguero, Francisco 
dc.date.accessioned2024-02-07T07:29:06Z
dc.date.available2024-02-07T07:29:06Z
dc.date.issued2018-12-18
dc.identifier.citationLiu, X.; Xu, Y.; Montes, R.; Dong, Y.; Herrera, F., Analysis of self-confidence indices-based additive consistency for fuzzy preference relations with self‐confidence and its application in group decision making. International Journal of Intelligent Systems, 34 (5), 920-946. (2019)es_ES
dc.identifier.urihttps://hdl.handle.net/10481/88497
dc.description.abstractEl artículo analiza la utilización de relaciones de preferencia difusas con autoconfianza (FPRs-SC) en problemas de toma de decisiones en grupo (GDM). El artículo se centra en el análisis de la consistencia aditiva de las FPRs-SC y su aplicación en GDM. Introduce leyes operativas para FPRs-SC, propone un índice de consistencia aditiva que considera tanto los valores de preferencia difusos como la autoconfianza, y presenta un algoritmo iterativo para tratar la inconsistencia en FPRs-SC. El estudio esboza un proceso para calcular FPR-SC colectivos agregando los individuales mediante un operador basado en índices de autoconfianza, dando más peso a los expertos más autoconfiados. Además, se diseña una función de puntuación de la autoconfianza para determinar la mejor alternativa en GDM con FPRs-SC. La viabilidad y validez de la investigación se demuestran mediante un ejemplo ilustrativo y análisis comparativos.es_ES
dc.description.abstractThe article discusses the utilization of fuzzy preference relations with self-confidence (FPRs-SC) in group decision-making (GDM) problems. The paper focuses on analyzing the additive consistency of FPRs-SC and its application in GDM. It introduces operational laws for FPRs-SC, proposes an additive consistency index considering both fuzzy preference values and self-confidence, and presents an iterative algorithm to address inconsistency in FPRs-SC. The study outlines a process to compute collective FPR-SC by aggregating individual ones using a self-confidence indices-based operator, giving more weight to the most self-confident experts. Additionally, a self-confidence score function is designed to determine the best alternative in GDM with FPRs-SC. The research's feasibility and validity are demonstrated through an illustrative example and comparative analyses.es_ES
dc.description.sponsorshipInstituto Interuniversitario de Investigación en Data Science and Computational Intelligence (DaSCI)es_ES
dc.language.isoenges_ES
dc.publisherWileyes_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 License
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectAdditive consistencyes_ES
dc.subjectFuzzy preference relations with self-confidence (FPRs-SC)es_ES
dc.subjectInduced ordered weighted averaging (IOWA)es_ES
dc.titleAnalysis of self-confidence indices-based additive consistency for fuzzy preference relations with self‐confidence and its application in group decision makinges_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1002/int.22081
dc.type.hasVersionSMURes_ES


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