Abstract
In this paper, we extend the Hamy mean (HM) operator and dual Hamy mean (DHM) operator with Pythagorean fuzzy numbers (PFNs) to propose Pythagorean fuzzy Hamy mean (PFHM) operator, weighted Pythagorean fuzzy Hamy mean (WPFHM) operator, Pythagorean fuzzy dual Hamy mean (PFDHM) operator, weighted Pythagorean fuzzy dual Hamy mean (WPFDHM) operator. Then the multiple attribute group decision making (MAGDM) methods are proposed with these operators. In the end, we utilize an applicable example for supplier selection to prove the proposed methods.
Highlights
Pythagorean fuzzy set (PFS) [1,2] has been designed with the membership degree and the non-membership degree, whose sum of squares is less than or equal to 1
Because Pythagorean fuzzy numbers (PFNs) can capture the fuzzy information and the Hamy mean (HM) can describe interrelationships among any number of arguments assigned by a variable vector, it is necessary to expand the HM and dual Hamy mean (DHM) operators to deal with the PFNs
In order to overcome this defect, we propose the weighted Pythagorean fuzzy dual Hamy mean (WPFDHM) operator
Summary
Pythagorean fuzzy set (PFS) [1,2] has been designed with the membership degree and the non-membership degree, whose sum of squares is less than or equal to 1. Khan et al [32] extend TOPSIS model with IVPFNs. Garg [33] defined the exponential operational laws of IVPFNs. Li and Zeng [34] gave some distance measure of PFNs. Gao [35] defined some hamacher prioritized operators in MADM with traditional prioritized aggregation operators [36,37,38,39,40,41]. Because PFNs can capture the fuzzy information and the HM can describe interrelationships among any number of arguments assigned by a variable vector, it is necessary to expand the HM and DHM operators to deal with the PFNs. how to fuse these PFNs with.
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