Approaches to manage hesitant fuzzy linguistic information based on the cosine distance and similarity measures for HFLTSs and their application in qualitative decision making

Hesitant fuzzy linguistic term set (HFLTS) is a set with ordered consecutive linguistic terms, and is very useful in addressing the situations where people are hesitant in providing their linguistic assessments. Wang [H. Wang, Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making, International Journal of Computational Intelligence Systems 8(1) (2015) 14–33.] removed the consecutive condition to introduce the notion of extended HFLTS (EHFLTS). The generalized form has wider applications in linguistic group decision-making. By introducing distance measures for EHFLTSs, in this paper we develop a novel multi-criteria group decision making model to deal with hesitant fuzzy linguistic information. The model collects group linguistic information by using EHFLTSs and avoids the possible loss of information. Moreover, it can assess the importance weights of criteria according to their subjective and objective information and rank alternatives based on the rationale of TOPSIS. In order to illustrate the applicability of the proposed algorithm, two examples are given and comparisons are made with the other existing methods.

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A multiple attribute decision making method based on free double hierarchy hesitant fuzzy linguistic information considering the prioritized and interactive attributes

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622020500467 ◽

2020 ◽

Author(s):

Peide Liu ◽

Mengjiao Shen ◽

Fei Teng ◽

Baoying Zhu ◽

Lili Rong

Keyword(s):

Decision Making ◽

Multiple Attribute Decision Making ◽

Linguistic Information ◽

Multiple Attribute ◽

Fuzzy Linguistic

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A Novel Method for Multiattribute Decision Making with Interval-Valued Pythagorean Fuzzy Linguistic Information

International Journal of Intelligent Systems ◽

10.1002/int.21881 ◽

2017 ◽

Vol 32 (10) ◽

pp. 1085-1112 ◽

Cited By ~ 58

Author(s):

Yuqin Du ◽

Fujun Hou ◽

Wasif Zafar ◽

Qian Yu ◽

Yubing Zhai

Keyword(s):

Decision Making ◽

Linguistic Information ◽

Novel Method ◽

Fuzzy Linguistic ◽

Interval Valued

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A Novel Decision-Making Model with Pythagorean Fuzzy Linguistic Information Measures and Its Application to a Sustainable Blockchain Product Assessment Problem

Sustainability ◽

10.3390/su11205630 ◽

2019 ◽

Vol 11 (20) ◽

pp. 5630 ◽

Cited By ~ 4

Author(s):

Feifei Jin ◽

Lidan Pei ◽

Huayou Chen ◽

Reza Langari ◽

Jinpei Liu

Keyword(s):

Decision Making ◽

Similarity Measure ◽

Membership Degree ◽

Linguistic Information ◽

Information Measures ◽

New Information ◽

Multi Attribute Decision Making ◽

Product Assessment ◽

Decision Making Model ◽

Fuzzy Linguistic

This study presents a novel multi-attribute decision-making (MADM) model on the basis of Pythagorean fuzzy linguistic information measures. To do so, we first present a new concept of Pythagorean fuzzy linguistic sets to describe fuzziness and inconsistent information, in which the Pythagorean fuzzy linguistic values (PFLVs) are represented by the linguistic membership degree and linguistic non-membership degree. Then, we introduce two axiomatic definitions of information measures for PFLVs, including Pythagorean fuzzy linguistic entropy and the Pythagorean fuzzy linguistic similarity measure, to measure the uncertainty degree of PFLVs and the similarity degree between among PFLVs. In addition, based on the logarithmic function, we construct two new information measure formulas and verify that they satisfy the axiomatic conditions of the Pythagorean fuzzy linguistic entropy and similarity measure, respectively. We further explore the relationship between the Pythagorean fuzzy linguistic entropy and similarity measure. Finally, we present a novel Pythagorean fuzzy linguistic MADM model with the Pythagorean fuzzy linguistic entropy and similarity measure. A numerical example of selecting the most desirable sustainable blockchain product is given, and a comparison with the existing approach was performed to validate the reliability of the developed decision-making model.

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