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Schweizer–Sklar Muirhead Mean Aggregation Operators Based on Pythagorean Fuzzy Sets and Their Application in Multi-criteria Decision-Making

In: Pythagorean Fuzzy Sets

Author

Listed:
  • Tahir Mahmood

    (International Islamic University Islamabad, Department of Mathematics and Statistics)

  • Zeeshan Ali

    (International Islamic University Islamabad, Department of Mathematics and Statistics)

Abstract

Schweizer–Sklar (SS) operations are more flexible to aggregate the information, and the Muirhead mean (MM) operator can examine the interrelationships among the family of attributes. MM operator is more proficient and more generalized than many aggregation operators to cope with awkward and inconsistence information in realistic decision issues. The objectives of this manuscript are to explore the SS operators based on Pythagorean fuzzy set (PFS) and studied their score function, accuracy function, and their relationships. Further, based on these operators, the MM operators based on PFS, called Pythagorean fuzzy MM (PFMM) operator, Pythagorean fuzzy weighted MM (PFWMM) operator, and their special cases are presented. Additionally, the multi-attribute decision-making (MADM) problem is solved by using the explored operators based on PFS to observe the consistency and efficiency of the discovered approach. Finally, the advantages, comparative analysis, and their geometrical representations are also discussed.

Suggested Citation

  • Tahir Mahmood & Zeeshan Ali, 2021. "Schweizer–Sklar Muirhead Mean Aggregation Operators Based on Pythagorean Fuzzy Sets and Their Application in Multi-criteria Decision-Making," Springer Books, in: Harish Garg (ed.), Pythagorean Fuzzy Sets, pages 235-259, Springer.
    • Handle: RePEc:spr:sprchp:978-981-16-1989-2_10
    DOI: 10.1007/978-981-16-1989-2_10
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