New q-rung orthopair fuzzy partitioned Bonferroni mean operators and their application in multiple attribute decision making

Wei Yang · Yongfeng Pang

127 citations0/0 files storedInternational Journal of Intelligent Systems

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Multi-Criteria Decision Making Rough Sets and Fuzzy Logic Fuzzy and Soft Set Theory

Abstract

The q-rung orthopair fuzzy sets are superior to intuitionistic fuzzy sets or Pythagorean fuzzy sets in expressing fuzzy and uncertain information. In this paper, some partitioned Bonferroni means (BMs) for q-rung orthopair fuzzy values have been developed. First, the q-rung orthopair fuzzy partitioned BM (q-ROFPBM) operator and the q-rung orthopair fuzzy partitioned geometric BM (q-ROFPGBM) operator are developed. Some desirable properties and some special cases of the new aggregation operators have been studied. The q-rung orthopair fuzzy weighted partitioned BM (q-ROFWPBM) operator and the q-rung orthopair fuzzy partitioned geometric weighted BM (q-ROFPGWBM) operator are also developed. Then, a new multiple-attribute decision-making method based on the q-ROFWPBM (q-ROFPGWBM) operator is proposed. Finally, a numerical example of investment company selection problem is given to illustrate feasibility and practical advantages of the new method.

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References

2016Generalized Orthopair Fuzzy Sets 2014Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets 2013Pythagorean Membership Grades, Complex Numbers, and Decision Making 2017Some q-Rung Orthopair Fuzzy Aggregation Operators and their Applications to Multiple-Attribute Decision Making 2016A New Generalized Pythagorean Fuzzy Information Aggregation Using Einstein Operations and Its Application to Decision Making 2015Pythagorean fuzzy TODIM approach to multi-criteria decision making 2015Fundamental Properties of Interval-Valued Pythagorean Fuzzy Aggregation Operators 2012Hesitant fuzzy geometric Bonferroni means

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