Cubical fuzzy geometric aggregation operators under confidence levels and their application in multiple criteria decision making

Cubical fuzzy set is more generous than picture and spherical fuzzy sets in expressing the uncertain information. In this study, confidence levels of the decision experts based on their familiarity of the evaluated objects is fused to the original information under cubical fuzzy environment. This paper concentrates on developing new cubical fuzzy geometric aggregation operators, namely, the confidence cubical fuzzy weighted and ordered weighted geometric aggregation operators by fusing the decision maker's familiarity information of the aggregated arguments. Some important properties of the proposed operators are also proved. Moreover, a multiple criteria decision making approach has been developed based on the developed operators. A real life problem of selecting a best enterprise resource planning system has been demonstrated to portray the influence of the proposed operators. Finally, the obtained results are compared with the existing operators to show the supremacy and uniqueness of the proposed operators.