Bipolar fuzzy Dombi prioritized aggregation operators in multiple attribute decision making

In this article, used Dombi t-norm (TN) and t-conorm (TCN) which can generate more complex and more flexible operation rules by adjusting a parameter to combine with prioritized aggregation operators (AOs) in bipolar fuzzy (BF) environment. In this study, introduced bipolar fuzzy Dombi prioritized AOs, namely bipolar fuzzy Dombi prioritized averaging operator, bipolar fuzzy Dombi geometric operator, bipolar fuzzy Dombi prioritized weighted averaging operator and bipolar fuzzy Dombi prioritized weighted geometric operator as these operators along with proofs to aggregate various preferences of the decision makers. Then, we investigated several properties of its. In this purpose, we designed a multiple attribute decision-making technique for the proposed study. Finally, an illustrative example is given to demonstrate proposed approach under BF environment and a sensitivity analysis is considered for the working parameter on the ordering of the alternatives. A comparative study is provided for the choice best decision of the proposed approach with the existing problems. Finally, it is concluded that the proposed approach gives a more practical nature to aggregate the information process during the data analysis, and hence they take an alternative way for solving decision-making problems.