Approaches to Multi-Attribute Group Decision Making Based on Induced Interval-Valued Pythagorean Fuzzy Einstein Aggregation Operator

K. Rahman (), A. Ali (), S. Abdullah () and F. Amin ()
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K. Rahman: Department of Mathematics, Hazara University Mansehra, KPK, Pakistan
A. Ali: Department of Mathematics, Hazara University Mansehra, KPK, Pakistan
S. Abdullah: #x2020;Department of Mathematics, Abdul Wali Khan University Mardan, Pakistan
F. Amin: Department of Mathematics, Hazara University Mansehra, KPK, Pakistan

New Mathematics and Natural Computation (NMNC), 2018, vol. 14, issue 03, 343-361

Abstract: Interval-valued Pythagorean fuzzy set is one of the successful extensions of the interval-valued intuitionistic fuzzy set for handling the uncertainties in the data. Under this environment, in this paper, we introduce the notion of induced interval-valued Pythagorean fuzzy Einstein ordered weighted averaging (I-IVPFEOWA) aggregation operator. Some of its desirable properties namely, idempotency, boundedness, commutatively, monotonicity have also been proved. The main advantage of using the proposed operator is that this operator gives a more complete view of the problem to the decision-makers. The method proposed in this paper provides more general, more accurate and precise results as compared to the existing methods. Therefore this method play a vital role in real world problems. Finally, we apply the proposed operator to deal with multi-attribute group decision- making problems under interval-valued Pythagorean fuzzy information. The approach has been illustrated with a numerical example from the field of the decision-making problems to show the validity, practicality and effectiveness of the new approach.

Keywords: Group decision making; interval-valued Pythagorean fuzzy set; Einstein operations laws; aggregation operator (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S1793005718500217

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