Please use this identifier to cite or link to this item:
Title: Hesitant Fuzzy Linguistic Terms Sets for Decision Making
Authors: Rodríguez, Rosa M.
Martínez, Luis
Herrera, Francisco
Abstract: Dealing with uncertainty is always a challenging problem, and different tools have been proposed to deal with it. Recently, a new model that is based on hesitant fuzzy sets has been presented to manage situations in which experts hesitate between several values to assess an indicator, alternative, variable, etc. Hesitant fuzzy sets suit the modeling of quantitative settings; however, similar situations may occur in qualitative settings so that experts think of several possible linguistic values or richer expressions than a single term for an indicator, alternative, variable, etc. In this paper, the concept of a hesitant fuzzy linguistic term set is introduced to provide a linguistic and computational basis to increase the richness of linguistic elicitation based on the fuzzy linguistic approach and the use of context-free grammars by using comparative terms. Then, a multicriteria linguistic decision-makingmodel is presented in which experts provide their assessments by eliciting linguistic expressions. This decision model manages such linguistic expressions by means of its representation using hesitant fuzzy linguistic term sets.
Keywords: Context-free grammar
fuzzy linguistic approach
hesitant fuzzy sets
linguistic decision making
linguistic information
Issue Date: Feb-2012
metadata.dc.description.sponsorship: Research Project TIN-2009-08286, P08-TIC-3548 y European fund for regional development
Publisher: IEEE
Citation: R. M. Rodriguez, L. Martinez and F. Herrera, Hesitant Fuzzy Linguistic Term Sets for Decision Making, IEEE Transactions on Fuzzy Systems, vol. 20, no. 1, pp. 109-119, Feb. 2012, doi: 10.1109/TFUZZ.2011.2170076.
Appears in Collections:DI-Artículos

Files in This Item:
File Description SizeFormat 
2012-Rodriguez et al-IEEETFS-vol20.pdfversión publicada407,54 kBAdobe PDFView/Open

This item is protected by original copyright