Robust Averaging–Geometric Aggregation Operators for Complex Intuitionistic Fuzzy Sets and Their Applications to MCDM Process

摘要

This paper presents aggregation operatorswhich encapsulate the interaction among the criteria and preferences under complexintuitionistic fuzzy (CIF) conditions. The current extensions of fuzzy set theory handle only the uncertain data by representingthe satisfaction and dissatisfaction degrees as real values and hence lose some information. A modification to these, CIF setsare portrayed by complex-valued membership degrees and can handle the data concurrently using additional terms, calledphase terms, which usually give knowledge related to periodicity. Motivated by the features of the CIF model, this paperstudies some aggregation operators, weighted averaging and geometric, for CIF sets and investigates their properties. Toease with the possible application, we explore the decision-making (DM) process in the CIF set environment and presentan algorithm to solve the multiple criteria DM problems. Finally, a practical example is presented to demonstrate the DMprocess based on the proposed operators and compared their performance with some similar approaches.