Decision-Making Approach under Pythagorean Fuzzy Yager Weighted Operators

Gulfam Shahzadi, Muhammad Akram and Ahmad N. Al-Kenani
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Gulfam Shahzadi: Department of Mathematics, University of the Punjab, New Campus, Lahore 54590, Pakistan
Muhammad Akram: Department of Mathematics, University of the Punjab, New Campus, Lahore 54590, Pakistan
Ahmad N. Al-Kenani: Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80219, Jeddah 21589, Saudi Arabia

Mathematics, 2020, vol. 8, issue 1, 1-20

Abstract: In fuzzy set theory, t -norms and t -conorms are fundamental binary operators. Yager proposed respective parametric families of both t -norms and t -conorms. In this paper, we apply these operators for the analysis of Pythagorean fuzzy sets. For this purpose, we introduce six families of aggregation operators named Pythagorean fuzzy Yager weighted averaging aggregation, Pythagorean fuzzy Yager ordered weighted averaging aggregation, Pythagorean fuzzy Yager hybrid weighted averaging aggregation, Pythagorean fuzzy Yager weighted geometric aggregation, Pythagorean fuzzy Yager ordered weighted geometric aggregation and Pythagorean fuzzy Yager hybrid weighted geometric aggregation. These tools inherit the operational advantages of the Yager parametric families. They enable us to study two multi-attribute decision-making problems. Ultimately we can choose the best option by comparison of the aggregate outputs through score values. We show this procedure with two practical fully developed examples.

Keywords: Yager operators; aggregation operators; arithmetic; geometric; decision-making (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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