Bipolar complex fuzzy credibility aggregation operators and their application in decision making problem

A bipolar complex fuzzy credibility set (BCFCS) is a new approach in computational intelligence and decision-making under uncertainty. Bipolar complex fuzzy credibility (BCFC) information has been employed as a strategy for dealing with confusing and unreliable situations that arise in everyday life. In this paper, we used the concept of aggregation operators to diagnose the well-known averaging and geometric aggregation operators, as well as evaluate some properties and related results. Using described operators, an algorithm for multiple criteria group decision making is proposed. Then, a numerical example of a case study of Hospital selection is discussed. Lastly, the comparative analysis of suggested operators with existing operators are also given to discuss the rationality, efficiency and applicability of these operators.

Automated summary

A bipolar complex fuzzy credibility set (BCFCS) is introduced as a new method in computational intelligence and decision-making under uncertainty. The use of bipolar complex fuzzy credibility (BCFC) information is proposed to handle confusing and unreliable situations in everyday life. Aggregation operators are employed to diagnose existing averaging and geometric aggregation operators and evaluate their properties and related results. An algorithm for multiple criteria group decision making is presented using the described operators. A numerical example of Hospital selection is discussed, and a comparative analysis of the suggested operators with existing operators is provided to examine their rationality, efficiency, and applicability.