New prioritized aggregation operators with priority degrees among priority orders for complex intuitionistic fuzzy information

Abstract

This paper aims to present some novel prioritized aggregation operators for aggregating complex intuitionistic fuzzy values (CIFVs). The aggregation operators are developed by assigning non-negative real numbers called as priority degrees among strict priority levels. The presented work is divided into three folds. The first fold is that uncertainties in the data are represented using CIFVs which have the characteristic of portraying membership and non-membership degrees over the unit disc of the complex plane. The second fold is to present prioritized averaging and geometric operators without priority degrees, prioritized averaging and geometric operators with priority degrees, prioritized ordered weighted averaging and geometric operators with priority degrees based on basic unit interval monotonic (BUM) function for aggregating dependent CIFVs. A number of propositions related to proposed operators are proved. The third fold is that a group decision-making approach based on proposed operators is developed and is applied on a decision-making problem. The results of proposed method are compared with several existing studies. The comparative study results reveal that the proposed approach is valid and gives fair results. The characteristics of the developed method are also compared with several existing approaches which highlight the superiority of the presented work over prevailing techniques. Besides this, the role of the priority degrees on aggregation result is also discussed in detail.