Multicriteria decision-making based on the confidence level Q-rung orthopair normal fuzzy aggregation operator

Q-rung orthopair fuzzy sets have been widely utilized in recent years to encounter uncertainties. At the same time, the idea of normal fuzzy numbers seems closer to human thinking. The notion of the Q-rung orthopair normal fuzzy set is a more flexible tool to capture the uncertainties because of the combined concept of Q-rung orthopair fuzzy sets and normal fuzzy numbers. This paper proposes some new weighted averaging, weighted geometric, ordered weighted averaging, and ordered weighted geometric aggregation operators for Q-rung orthopair normal fuzzy numbers, which also comprise the confidence level for the alternatives given by the decision-maker. We then introduce a multicriteria decision-making approach based on these operators to get more rational results than the existing approaches. Furthermore, to prove the superiority of the proposed approach, a comparative analysis with the different existing methods has also been done. Finally, sensitivity analyses on the parameter Q and the confidence level of Q-rung orthopair normal fuzzy numbers have been demonstrated to highlight the importance of these parameters and to show the stability of the proposed method.