Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/30754
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dc.contributor.authorSalas-Molina, Francisco-
dc.contributor.authorReig-Mullor, Javier-
dc.contributor.authorPla-Santamaría, David-
dc.contributor.authorGarcía-Bernabeu, Ana-
dc.contributor.otherDepartamentos de la UMH::Estudios Económicos y Financieroses_ES
dc.date.accessioned2024-01-26T11:27:41Z-
dc.date.available2024-01-26T11:27:41Z-
dc.date.created2023-10-
dc.identifier.citationIranian Journal of Fuzzy Systems, Volume 20, Number 6, (2023), pp. 137-153es_ES
dc.identifier.issn1735-0654-
dc.identifier.urihttps://hdl.handle.net/11000/30754-
dc.description.abstractRanking fuzzy numbers have become of growing importance in recent years, especially as decision-making is increasingly performed under greater uncertainty. In this paper, we extend the concept of magnitude to rank fuzzy numbers to a more general definition to increase in flexibility and generality. More precisely, we propose a multidimensional approach to rank fuzzy numbers considering alternative magnitude definitions with three novel features: multidimensionality, normalization, and a ranking based on a parametric distance function. A multidimensional magnitude definition allows us to consider multiple attributes to represent and rank fuzzy numbers. Normalization prevents meaningless comparison among attributes due to scaling problems, and the use of the parametric Minkowski distance function becomes a more general and flexible ranking approach. The main contribution of our multidimensional approach is the representation of a fuzzy number as a point in a $n$-dimensional normalized space of attributes in which the distance to the origin is the magnitude value. We illustrate our methodology and provide further insights into different normalization approaches and parameters through several numerical examples. Finally, we describe an application of our ranking approach to a multicriteria decision-making problem within an economic context in which the main goal is to rank a set of credit applicants considering different financial ratios used as evaluation criteria.es_ES
dc.formatapplication/pdfes_ES
dc.format.extent17es_ES
dc.language.isoenges_ES
dc.publisherUniversity of Sistan and Baluchestanes_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRankinges_ES
dc.subjectmagnitudees_ES
dc.subjectmultiple dimensionses_ES
dc.subjectnormalizationes_ES
dc.subjectfuzzy economicses_ES
dc.subjectcredit rankinges_ES
dc.subject.classificationEconomía financiera y contabilidades_ES
dc.subject.otherCDU::3 - Ciencias sociales::33 - Economíaes_ES
dc.titleA multidimensional approach to rank fuzzy numbers based on the concept of magnitudees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.22111/IJFS.2023.43939.7738es_ES
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Artículos Estudios Económicos y Financieros


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