Pythagorean fuzzy preference relations and their applications in group decision‐making systems

In this paper, we introduce a new type of fuzzy preference structure, called Pythagorean fuzzy preference relations (PFPRs), to describe uncertain evaluation information in group decision‐making process. Moreover, it allows decision makers to offer effectively handle uncertain information more flexibly than intuitionistic fuzzy preference relations when one compares two alternatives in the process of decision making. Using PFPRs, we propose an approach for group decision making based on group recommendations and consistency matrices. First, the proposed approach constructs the collective consistency matrix, the weight collective preference relations (PRs), and the group collective PR. Then, it construct a consensus relation for each expert and determinate the group consensus degree for all experts. If the group consensus degree is smaller than a predefined threshold value, then it identify the consensus values in each consensus relation which are smaller than the group consensus degree and updates the Pythagorean fuzzy preference values corresponding to the identified consensus values. The above process is continued, until the group consensus degree is larger than or equal to the predefined threshold value. Finally, based on the group collective PR, we calculate the row arithmetic mathematical average values and with respect to that values the various methods are applied for ranking the preference order of the alternatives. Numerical example are provided to illustrate the proposed approach.

[1]  Zeshui Xu,et al.  Intuitionistic preference relations and their application in group decision making , 2007, Inf. Sci..

[2]  Ronald R. Yager,et al.  Pythagorean Membership Grades, Complex Numbers, and Decision Making , 2013, Int. J. Intell. Syst..

[3]  Ronald R. Yager,et al.  Pythagorean Membership Grades in Multicriteria Decision Making , 2014, IEEE Transactions on Fuzzy Systems.

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

[5]  Shyi-Ming Chen,et al.  Group decision making using incomplete fuzzy preference relations based on the additive consistency and the order consistency , 2014, Inf. Sci..

[6]  Zeshui Xu,et al.  Alternative queuing method for multiple criteria decision making with hybrid fuzzy and ranking information , 2016, Inf. Sci..

[7]  Li-Wei Lee,et al.  Group decision making with incomplete fuzzy preference relations based on the additive consistency and the order consistency , 2012, Expert Syst. Appl..

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

[9]  Zeshui Xu,et al.  Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets , 2014, Int. J. Intell. Syst..

[10]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[11]  T. Tanino Fuzzy preference orderings in group decision making , 1984 .

[12]  Omolbanin Yazdanbakhsh,et al.  On Pythagorean and Complex Fuzzy Set Operations , 2016, IEEE Transactions on Fuzzy Systems.

[13]  Xiaolu Zhang,et al.  Multicriteria Pythagorean fuzzy decision analysis: A hierarchical QUALIFLEX approach with the closeness index-based ranking methods , 2016, Inf. Sci..

[14]  Tien-Chin Wang,et al.  Multi-criteria decision making with fuzzy linguistic preference relations , 2011 .

[15]  Enrique Herrera-Viedma,et al.  Confidence-consistency driven group decision making approach with incomplete reciprocal intuitionistic preference relations , 2015, Knowl. Based Syst..

[16]  Zeshui Xu,et al.  On Compatibility of Interval Fuzzy Preference Relations , 2004, Fuzzy Optim. Decis. Mak..

[17]  Francisco Herrera,et al.  Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations , 1998, Fuzzy Sets Syst..