COMPLEX INTERVAL VALUED PYTHAGOREAN FUZZY ACZEL ALSINA AGGREGATION OPERATORS WITH APPLICATIONS

Abstract

The common mathematical tool for combining several inputs into a single, unique result is an aggregation operator. The study introduces various aggregation operator (AOs) designed for complex interval valued Pythagorean fuzzy information. The complex interval valued Pythagorean fuzzy sets (CIVPyFS) which was created lately, proves to be a useful tool for expressing obscurity and ambiguities. The complex interval valued Pythagorean fuzzy sets have a wide range of applications in routine decision-making procedures because of their improved ability to handle uncertain circumstances compared to other fuzzy set theories. In this article, novel AOs are developed considering the advantages of the CIVPyFS to handle the multi-criteria decision-making challenges. The new AOs consider the relations between two input arguments. To improve the adaptability of the new AOs, this article incorporates the Aczel-Alsina (AA) operations. This study proposes the CIVPyF  Aczel-Alsina Heronian mean (CIVPyFAAHM) operator, CIVPyF  Aczel-Alsina geometric Heronian mean (CIVPyFAAGHM) operator which combines the Aczel-Alsina operational rules with the and Heronian mean/geometric Heronian mean operators. Various properties of the AOs are investigated. Further, weighted form these AOs are introduced. Then, we set up the MCDM technique using the two AOs that are suggested to solve MCDM problems under CIVPyFS environment. We next illustrate the efficacy and suitability of the predicted approach with a numerical example and compare it with other relevant MCDM strategies presently in existence in the CIVPyF information.