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Multi-attribute decision making for power Dombi operators under Pythagorean fuzzy information with MABAC method

Abstract

Pythagorean fuzzy sets have a lot of applications in the field of engineering and scientific problems. Also, besides, the power averaging (PA) operator can reduce the influence of evaluating extreme data from some bias experts. Dombi operator has flexibility in working on parameter evaluation. Here, Dombi operations combined with PA operator are used to construct some Pythagorean fuzzy power Dombi operators, i.e. Pythagorean fuzzy power Dombi weighted averaging (PFPDWA), order weighted averaging and hybrid weighted averaging operators have been introduced. Further, Pythagorean fuzzy power Dombi weighted geometric (PFPDWG), order weighted geometric and hybrid weighted geometric operators have been considered. Meanwhile, some properties of these operators have been established in detail. To solve the Pythagorean fuzzy multiple attribute decision making problem by using PFPDWA and PFPDWG operators to design an algorithm for the proposed approach. At the same time, a novel approach is proposed to design multiple attribute border approximation area comparison approached with Pythagorean fuzzy numbers to justify the feasibility of the proposed approach. Finally, we compare the developed approach with some existing operators to show its efficiency.

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Acknowledgements

The authors wish to thank the anonymous reviewers for their valuable comments and helpful suggestions which greatly improved the quality of this paper.

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Correspondence to Chiranjibe Jana.

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Jana, C., Garg, H. & Pal, M. Multi-attribute decision making for power Dombi operators under Pythagorean fuzzy information with MABAC method. J Ambient Intell Human Comput (2022). https://doi.org/10.1007/s12652-022-04348-0

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Keywords

  • Pythagorean fuzzy numbers
  • Dombi operation and power operators
  • Pythagorean fuzzy power Dombi weighted averaging
  • Pythagorean fuzzy power Dombi weighted geometric operator
  • MABAC approach with PFNs
  • Multiple attribute decision making approach