Linguistic multi-criteria decision-making model with output variable expressive richness
dc.cclicence | CC-BY-NC-ND | en |
dc.contributor.author | Herrera-Viedma, Enrique | en |
dc.contributor.author | Chiclana, Francisco | en |
dc.contributor.author | Cid-Lopez, Andres | en |
dc.contributor.author | Hornos, Miguel J. | en |
dc.contributor.author | Carrasco, Ramon Alberto | en |
dc.date.acceptance | 2017-04-24 | en |
dc.date.accessioned | 2017-05-09T09:40:25Z | |
dc.date.available | 2017-05-09T09:40:25Z | |
dc.date.issued | 2017-04-26 | |
dc.description | The 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.abstract | In 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.funder | European Regional Development Fund | en |
dc.identifier.citation | Cid-Lopez, A. et al. (2017) Linguistic multi-criteria decision-making model with output variable expressive richness. Expert Systems with Applications. 83, pp. 350-362 | en |
dc.identifier.doi | https://doi.org/10.1016/j.eswa.2017.04.049 | |
dc.identifier.uri | http://hdl.handle.net/2086/14153 | |
dc.language.iso | en | en |
dc.peerreviewed | Yes | en |
dc.projectid | TIN2016-75850-R | en |
dc.projectid | TIN2016-79484-R | en |
dc.projectid | TIN2013-40658-P | en |
dc.publisher | Elsevier | en |
dc.researchgroup | Centre for Computational Intelligence | en |
dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
dc.subject | multi-criteria decision making | en |
dc.subject | linguistic labels | en |
dc.subject | variable expressive richness | en |
dc.subject | 2-tuple representation | en |
dc.subject | linguistic TOPSIS model | en |
dc.title | Linguistic multi-criteria decision-making model with output variable expressive richness | en |
dc.type | Article | en |
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