Multiple attributes group decision-making based on trigonometric operators, particle swarm optimization and complex intuitionistic fuzzy values

This paper describes a novel multi-attribute group decision-making (MAGDM) algorithm based on complex intuitionistic fuzzy values (CIFVs). The present work is divided into three parts. In the first part, the uncertainties in the data are expressed in CIFVs with two membership degrees over the unit disc of the complex plane. The second part states some new operational laws based on tangential functions and the aggregation operators to aggregate the different CIFVs. The properties related to the proposed operations and operators are studied. A nonlinear multi-objective optimization model has been formulated by considering the maximizing and minimizing satisfaction and dissatisfaction degrees respectively to derive the attribute weights for the MAGDM problems. The model has been solved using the particle swarm optimization algorithm. Finally, a numerical example illustrates a MAGDM algorithm based on proposed operators. The reliability and effectiveness of the proposed method is explored by comparing it with several general studies.