Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the-art survey

H Liao, Z Xu, E Herrera-Viedma, F Herrera - International Journal of Fuzzy …, 2018 - Springer
International Journal of Fuzzy Systems, 2018Springer
The hesitant fuzzy linguistic term set (HFLTS) has gained great success as it can be used to
represent several linguistic terms or comparative linguistic expressions together with some
context-free grammars. This new approach has enabled the analysis and computing of
linguistic expressions with uncertainties and opened the door for the possibility to develop
more comprehensive and powerful decision theories and methods based on linguistic
knowledge. Lots of new approaches and proposals for decision-making problems have …
Abstract
The hesitant fuzzy linguistic term set (HFLTS) has gained great success as it can be used to represent several linguistic terms or comparative linguistic expressions together with some context-free grammars. This new approach has enabled the analysis and computing of linguistic expressions with uncertainties and opened the door for the possibility to develop more comprehensive and powerful decision theories and methods based on linguistic knowledge. Lots of new approaches and proposals for decision-making problems have been proposed to overcome the limitations of previous linguistic decision-making approaches. Now and in the future, decision-making methodologies and algorithms with hesitant fuzzy linguistic models would be a quite promising research line representing a high-quality breakthrough in this topic. To facilitate the study on HFLTS theory, this paper makes a state-of-the-art survey on HFLTSs based on the 134 selected papers from Web of Sciences published from January 2012 to October 2017. We justify the motivation, definitions, operations, comparison methods and measures of HFLTSs. We also summarize the different extensions of HFLTSs. The studies on multiple criteria decision making (MCDM) with HFLTSs in terms of aggregation operators and MCDM methods are clearly reviewed. We also conduce some overviews on decision making with hesitant fuzzy linguistic preference relations. The applications, research challenges and future directions are also given.
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