New ranking order for linguistic hesitant fuzzy sets

Abstract Linguistic hesitant fuzzy sets (LHFSs) can effectively represent the qualitative and quantitative hesitant judgements of decision-makers. Several ranking methods have been proposed to demonstrate the application of LHFSs. However, none of them can rank LHFSs logically. Hence, this short communication first analyses the disadvantages of previous ranking methods in terms of theoretical and numerical aspects. A new ranking order is then proposed to address such shortcomings. Finally, a numerical example is presented to demonstrate the specific application of the new method and compare it with previous ones.

[1]  Fanyong Meng,et al.  Correlation Coefficient of Interval-Valued Intuitionistic Uncertain Linguistic Sets and Its Application , 2017, Cybern. Syst..

[2]  Qiang Zhang,et al.  Multi-attribute decision analysis under a linguistic hesitant fuzzy environment , 2014, Inf. Sci..

[3]  Lin Li,et al.  A multi-criteria decision-making model for hotel selection with linguistic distribution assessments , 2017, Appl. Soft Comput..

[4]  Luis Martínez-López,et al.  An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making , 2016, Int. J. Comput. Intell. Syst..

[5]  Hong-yu Zhang,et al.  A likelihood-based TODIM approach based on multi-hesitant fuzzy linguistic information for evaluation in logistics outsourcing , 2016, Comput. Ind. Eng..

[6]  Chen Wang,et al.  Linguistic Interval Hesitant Fuzzy Sets and Their Application in Decision Making , 2015, Cognitive Computation.

[7]  Hong-yu Zhang,et al.  Multi-criteria decision-making methods based on the Hausdorff distance of hesitant fuzzy linguistic numbers , 2015, Soft Computing.

[8]  Hong-yu Zhang,et al.  Hesitant Fuzzy Linguistic Maclaurin Symmetric Mean Operators and their Applications to Multi‐Criteria Decision‐Making Problem , 2018, Int. J. Intell. Syst..

[9]  Zhang-peng Tian,et al.  A multihesitant fuzzy linguistic multicriteria decision-making approach for logistics outsourcing with incomplete weight information , 2018, Int. Trans. Oper. Res..

[10]  Francisco Herrera,et al.  Theory and Methodology Choice functions and mechanisms for linguistic preference relations , 2000 .

[11]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[12]  Hong-yu Zhang,et al.  Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems , 2014, Inf. Sci..

[13]  Zeshui Xu,et al.  Hesitant fuzzy information aggregation in decision making , 2011, Int. J. Approx. Reason..

[14]  Hong-yu Zhang,et al.  Distance-Based Multi-Criteria Group Decision-Making Approaches with Multi-Hesitant Fuzzy Linguistic Information , 2017, Int. J. Inf. Technol. Decis. Mak..

[15]  Zeshui Xu,et al.  Interval-valued hesitant preference relations and their applications to group decision making , 2013, Knowl. Based Syst..

[16]  Xiaohong Chen,et al.  A Multi-Criteria Decision-Making Method Based on Heronian Mean Operators Under a Linguistic Hesitant Fuzzy Environment , 2015, Asia Pac. J. Oper. Res..

[17]  Xiao-hong Chen,et al.  Fuzzy Multichoice Games with Fuzzy Characteristic Functions , 2017 .

[18]  Hong-yu Zhang,et al.  Multi-criteria decision-making approaches based on distance measures for linguistic hesitant fuzzy sets , 2016, J. Oper. Res. Soc..

[19]  Fanyong Meng,et al.  Decision making with intuitionistic linguistic preference relations , 2019, Int. Trans. Oper. Res..

[20]  Hong-yu Zhang,et al.  Linguistic hesitant fuzzy multi-criteria decision-making method based on evidential reasoning , 2016, Int. J. Syst. Sci..

[21]  Francisco Herrera,et al.  Hesitant Fuzzy Linguistic Term Sets for Decision Making , 2012, IEEE Transactions on Fuzzy Systems.

[22]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[23]  Radko Mesiar,et al.  Hesitant L ‐Fuzzy Sets , 2017, Int. J. Intell. Syst..