A new type of preference relations: Fuzzy preference relations with self-confidence

dc.cclicenceCC-BY-NCen
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.contributor.authorCabrerizo, F. J.en
dc.contributor.authorLiu, Wenquen
dc.contributor.authorDong, Y.en
dc.date.accessioned2016-04-14T13:41:13Z
dc.date.available2016-04-14T13:41:13Z
dc.date.issued2016
dc.description.abstractPreference relations are very useful to express decision makers’ preferences over alternatives in the process of decision-making. However, multiple self-confidence levels are not considered in existing preference relations. In this study, we propose a new type of preference relations: fuzzy preference relations with self-confidence. A linear programming model is proposed for estimating priority vectors of this new type of preference relations. Finally, two numerical examples are provided to demonstrate the linear programming model, and a comparative analysis is used to show the influence of self-confidence levels on the decision-making results.en
dc.funderThis work was supported in part by NSF of China under Grants Nos. 71171160 and 71571124, FEDER funds under Grant TIN2013-40658-P, and the Andalusian Excellence Project Grant TIC-5991.en
dc.identifier.citationLi, Q. et al. (2016) A new type of preference relations: Fuzzy preference relations with self-confidence. Accepted for presentation at FUZZ-IEEE2006 (WCCI2016).en
dc.identifier.doihttps://doi.org/10.1109/fuzz-ieee.2016.7737892
dc.identifier.urihttp://hdl.handle.net/2086/11897
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidNSF of China Grants Nos. 71171160 and 71571124; FEDER Grant TIN2013-40658-P; Andalusian Excellence Project Grant TIC-5991.en
dc.publisherIEEEen
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.titleA new type of preference relations: Fuzzy preference relations with self-confidenceen
dc.typeConferenceen

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
PID4162833.pdf
Size:
238.86 KB
Format:
Adobe Portable Document Format
Description:
Authors' copy of the final accepted paper.
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
4.2 KB
Format:
Item-specific license agreed upon to submission
Description: