A Consistency Check Method for Trusted Hesitant Fuzzy Sets with Confidence Levels Based on a Distance Measure

This paper proposes a consistency check method for hesitant fuzzy sets with confidence levels by employing a distance measure. Firstly, we analyze the difference between each fuzzy element and its corresponding attribute comprehensive decision value and then obtain a comprehensive distance measure for each attribute. Subsequently, by taking the relative credibility as the weight, we assess the consistency of hesitant fuzzy sets. Finally, numerical examples are put forward to verify the effectiveness and reliability of the proposed method.

[1]  Shanlin Yang,et al.  The group consensus based evidential reasoning approach for multiple attributive group decision analysis , 2010, Eur. J. Oper. Res..

[2]  Wenyi Zeng,et al.  New distance and similarity measures on hesitant fuzzy sets and their applications in multiple criteria decision making , 2015, Eng. Appl. Artif. Intell..

[3]  Bijan Sarkar,et al.  Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain , 2017, Comput. Ind. Eng..

[4]  B. Farhadinia,et al.  Distance and similarity measures for higher order hesitant fuzzy sets , 2014, Knowl. Based Syst..

[5]  Ligang Zhou,et al.  Interval-Valued Pythagorean Hesitant Fuzzy Set and Its Application to Multiattribute Group Decision-Making , 2020, Complex..

[6]  Wenyi Zeng,et al.  Distance and similarity measures between hesitant fuzzy sets and their application in pattern recognition , 2016, Pattern Recognit. Lett..

[7]  Francisco Herrera,et al.  A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations , 2007, IEEE Transactions on Fuzzy Systems.

[8]  Enrique Herrera-Viedma,et al.  A Consensus Model for Group Decision Making Problems with Unbalanced Fuzzy Linguistic Information , 2009, Int. J. Inf. Technol. Decis. Mak..

[9]  Janusz Kacprzyk,et al.  A consensus‐reaching process under intuitionistic fuzzy preference relations , 2003, Int. J. Intell. Syst..

[10]  Zeshui Xu,et al.  Distance and similarity measures for hesitant fuzzy sets , 2011, Inf. Sci..

[11]  Zeshui Xu,et al.  On distance and correlation measures of hesitant fuzzy information , 2011, Int. J. Intell. Syst..

[12]  Changyong Liang,et al.  Multiple Attributes Group Decision-Making Approaches Based on Interval-Valued Dual Hesitant Fuzzy Unbalanced Linguistic Set and Their Applications , 2018, Complex..

[13]  Zeshui Xu,et al.  Induced Aggregation under Confidence Levels , 2011, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[14]  Gloria Bordogna,et al.  A linguistic modeling of consensus in group decision making based on OWA operators , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[15]  Yejun Xu,et al.  Consistency test and weight generation for additive interval fuzzy preference relations , 2013, Soft Computing.

[16]  Shouzhen Zeng,et al.  A method based on TOPSIS and distance measures for hesitant fuzzy multiple attribute decision making , 2018 .

[17]  Francisco Herrera,et al.  A model of consensus in group decision making under linguistic assessments , 1996, Fuzzy Sets Syst..

[18]  Francisco Herrera,et al.  A rational consensus model in group decision making using linguistic assessments , 1997, Fuzzy Sets Syst..

[19]  Luis Martínez-López,et al.  A Consensus Support System Model for Group Decision-Making Problems With Multigranular Linguistic Preference Relations , 2005, IEEE Transactions on Fuzzy Systems.

[20]  Meng Zhao,et al.  A Method Adjusting Consistency and Consensus for Group Decision-Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers , 2018, Complex..

[21]  Wenyi Zeng,et al.  Note on distance measure of hesitant fuzzy sets , 2015, Inf. Sci..

[22]  Xin Wang,et al.  Multicriteria Decision Making Based on Archimedean Bonferroni Mean Operators of Hesitant Fermatean 2-Tuple Linguistic Terms , 2019, Complex..