Novel Dual Partitioned Maclaurin Symmetric Mean Operators for the Selection of Computer Network Security System With Complex Intuitionistic Fuzzy Setting

Abstract

Intuitionistic fuzzy sets (IFSs) are key concepts in ambiguity and uncertainty. However, IFSs deal only with anticipation, not periodicity. To do so, complex intuitionistic fuzzy sets (CIFS) can handle uncertainties and periodicity simultaneously. Also, the Maclaurin symmetric mean (MSM) operator is a better tool for dealing with the criteria's interrelationships. As a result, this article presents a multi-criteria decision-making (MCDM) approach in the CIFS setting, which draws inspiration from the CIFS and MSM operators. We develop complex intuitionistic fuzzy partitioned dual Maclaurin symmetric mean (CIFPDMSM) operators and their weighted form by considering that all the criteria can be arranged into some groups. The proposed operators deal not only with interrelationships between criteria but also with partitioned relationships among criteria. Some properties of the proposed operators are discussed in detail. Further, an MCDM approach is developed based on the proposed operators in the CIFS environment. To show the effectiveness and application of the developed method, we also present a numerical example for selecting computer network security systems. Finally, the method is compared with the existing technique to demonstrate the proposed method's applicability and feasibility.