Multi-criteria Radio Frequency Identification Approach for Manufacturing Company Selection Based on Partitioned Maclaurin Symmetric Mean Operators Under Complex Intuitionistic Fuzzy Set Environment

The theory of intuitionistic fuzzy sets (IFSs) plays an essential role to deal with uncertainty and ambiguity. However, the IFSs deal only with anticipation, not periodicity. But, complex IFSs (CIFS) can handle both uncertainties and periodicity at a time. Therefore, this paper focuses on a new multi-criteria decision making (MCDM) approach using Maclaurin symmetric mean (MSM) operator in connection with the CIFS setting. Then, we develop some CIF partitioned based MSM (CIFPMSM) operators and their weighted form by considering that all the criteria can be arranged into some groups. The proposed operators not only deal with the interrelationship among criteria but also deal with the partitioned relationship among criteria. We discuss the properties of these proposed operators and investigate their cases. Finally, a decision-making approach for radio frequency identification (RFID) for manufacturing companies is developed based on the proposed operators and compared the results with the existing method to show the application and feasibility of the proposed method.