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dc.contributor.authorHerrera-Viedma, Enriqueen
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorCid-Lopez, Andresen
dc.contributor.authorHornos, Miguel J.en
dc.contributor.authorCarrasco, Ramon Albertoen
dc.date.accessioned2017-05-09T09:40:25Z
dc.date.available2017-05-09T09:40:25Z
dc.date.issued2017-04-26
dc.identifier.citationCid-Lopez, A. et al. (2017) Linguistic multi-criteria decision-making model with output variable expressive richness. Expert Systems with Applications. 83, pp. 350-362en
dc.identifier.urihttp://hdl.handle.net/2086/14153
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractIn general, traditional decision-making models are based on methods that perform calculations on quantitative measures. These methods are usually applied to assess possible solutions to a problem, resulting in a ranking of alternatives. However, when it comes to making decisions about qualitative measures –such as service quality–, the quantitative assessment is a bit difficult to interpret. Therefore, taking into account the maturity of the linguistic assessment models, this paper puts forth a new solution proposal. It is a decision-making model that uses linguistic labels –represented with the 2-tuple notation– and a variable expressive richness when providing output results. This solution allows expressing results in a manner closer to the human cognitive system. To achieve this goal, a mechanism has been implemented for measuring the distance among the aggregate ratings, providing the decision-maker with a fast and intuitive answer. The proposal is illustrated with an application example based on the TOPSIS model, using linguistic labels throughout the entire process.en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectmulti-criteria decision makingen
dc.subjectlinguistic labelsen
dc.subjectvariable expressive richnessen
dc.subject2-tuple representationen
dc.subjectlinguistic TOPSIS modelen
dc.titleLinguistic multi-criteria decision-making model with output variable expressive richnessen
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1016/j.eswa.2017.04.049
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderEuropean Regional Development Funden
dc.projectidTIN2016-75850-Ren
dc.projectidTIN2016-79484-Ren
dc.projectidTIN2013-40658-Pen
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2017-04-24en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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