Abstract
Keeping in mind the importance and well growing Pythagorean fuzzy sets, in this paper, some novel operators for Pythagorean fuzzy sets and their properties are demonstrated. In this paper, we develop a comprehensive model to tackle decision-making problems where strong points of view are in the favour and against the some projects, entities or plans. Therefore, a new approach, based on Pythagorean fuzzy set models by means of Pythagorean fuzzy Dombi aggregation operators is proposed. An approach to deal with decision-making problems using Pythagorean Dombi averaging and Dombi geometric aggregation operators is established. This model has a stronger capability than existing averaging, geometric, Einstein, logarithmic averaging and logarithmic geometric aggregation operators for Pythagorean fuzzy information. Finally, the proposed method is demonstrated through an example of how the proposed method helps us and is effective in decision-making problems.
Highlights
This universe is loaded with qualms, imprecision and unclearness
Yager enquired about this scenario in [3,4] and improved the concept of intuitionistic fuzzy sets (IFSs) to Pythagorean fuzzy sets (PFSs), which could be considered as a generalization of IFSs
Steps 2 and 3: we find the score value of each alternative and their ranking as follows: Looking at the illustration above, it is evident that, though overall ranking values of the alternatives are dissimilar, due to the usage of two Dombi aggregation operators, the ranking order regarding the alternatives are analogous, and the most desirable alternative is
Summary
This universe is loaded with qualms, imprecision and unclearness. In reality, the greater part of the ideas we encounter in daily life are more unclear than exact. A more comprehensive model is required for such situations Yager enquired about this scenario in [3,4] and improved the concept of IFSs to Pythagorean fuzzy sets (PFSs), which could be considered as a generalization of IFSs. The main difference between IFSs. Symmetry 2019, 11, 383 and PFSs is that, in IFSs, the sum of membership and non-membership is always from unit closed interval, but, in PFSs, the sum of squares of membership grade and non-membership grade are real numbers between 0 and 1. Ye [16] firstly defined a Dombi aggregation operator for linguistic cubic variables, and a multiple attribute decision-making (MADM) method is developed in linguistic cubic setting
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