Ranking method of the generalized intuitionistic fuzzy numbers founded on possibility measures and its application to MADM problem

In the real number set, generalized intuitionistic fuzzy numbers (GIFNs) are an impressive number of fuzzy sets (FSs). GIFNs are very proficient in managing the decision-making problem data. Our aim of this paper is to develop a new ranking method for solving a multi-attribute decision-making (MADM) problem with GIFN data. Here, we have defined the possibility mean and standard deviation of GIFNs. Then, we have formulated the magnitude of membership and non-membership function of GIFNs. In the proposed MADM problem, the attribute values are expressed as GIFNs, which is a very workable environment for decision-making problems. Finally, a numerical example is analyzed to demonstrate the flexibility, applicability and universality of the proposed ranking method and MADM problem.