Complex intuitionistic fuzzy preference relations and their applications in individual and group decision‐making problems

This paper aspires to present single and group decision-making methods based on complex intuitionistic fuzzy (CIF) preference relations (CIFPRs). The presented work is divided into three folds. The first fold is that the concept of CIFPRs is introduced in this study in which the pairwise comparison values are represented using CIF numbers which have the characteristic of portraying membership and nonmembership degrees over the unit disc of the complex plane. The conditions for additive consistent CIFPR are defined and the related results are explored. In addition, an algorithm for rectifying inconsistent CIFPR is also developed. The second fold is that two goal programming models are established for generating CIF normalized priority weights corresponding to individual and group decision-making problems. The third fold is to develop the algorithms for handling individual and group decision-making problems with CIFPRs. The practicality of the proposed algorithms is shown by applying them to real-life decision-making problems. The results of the presented methods are compared with several existing studies.