Trapezoidal intuitionistic fuzzy Bonferroni means and its application in multi-attribute decision making

The aim of this study is to investigate Bonferroni mean (BM) aggregation operator under intuitionistic trapezoidal fuzzy environment. BM operator is more applicable in decision making process due to the fact that it has the capability to capture the interrelationship between input arguments. In view of this, a trapezoidal intuitionistic fuzzy BM (TrIFBM) operator is developed here, which is represented as trapezoidal intuitionistic fuzzy numbers (TrIFNs). The desirable properties of TrIFBM are also studied. Further, TrIFBM has been generalized by replacing its inner and outer mean with other type aggregation operators. To explore its modeling capability some examples have been given. A new ranking method of TrIFNs has been proposed. Finally, weighted TrIFBM is developed and a multi-attribute decision making (MADM) technique is proposed. A practical example is presented to illustrate the application of weighted TrIFBM in MADM.