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Granular Computing
Published in: Granular Computing 3/2020

27-04-2019 | Original Paper

New approach to multiple attribute group decision-making based on Pythagorean fuzzy Einstein hybrid geometric operator

Authors: Khaista Rahman, Asad Ali

Published in: Granular Computing | Issue 3/2020

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Abstract

The objective of the present work is divided into two folds. Firstly, Pythagorean fuzzy Einstein hybrid geometric operator has been introduced along with their properties, namely idempotency, boundedness and monotonicity. Actually, Pythagorean fuzzy Einstein weighted geometric aggregation operator weighs only the Pythagorean fuzzy arguments, and Pythagorean fuzzy Einstein ordered weighted geometric aggregation operator weighs only the ordered positions of the Pythagorean fuzzy arguments instead of weighing the Pythagorean fuzzy arguments themselves. To overcome these limitations, we introduce the concept of Pythagorean fuzzy Einstein hybrid geometric aggregation operator, which weighs both the given Pythagorean fuzzy value and its ordered position. Thus, the main advantage of the proposed operator is that it is the generalization of their existing operators. Therefore, this method plays a vital role in real-world problems. Finally, we applied the proposed operator to multiple-attribute group decision-making.
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Metadata
Title
New approach to multiple attribute group decision-making based on Pythagorean fuzzy Einstein hybrid geometric operator
Authors
Khaista Rahman
Asad Ali
Publication date
27-04-2019
Publisher
Springer International Publishing
Published in
Granular Computing / Issue 3/2020
Print ISSN: 2364-4966
Electronic ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-019-00166-6

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