Intuitionistic fuzzy multi-criteria decision making with application to job hunting: A comparative perspective

The existing intuitionistic fuzzy information aggregation methods based on power mean cannot work well when the membership or non-membership degree of the intuitionistic fuzzy numbers (IFNs) reduced to zero. For solving the considered problem effectively, a group of new power intuitionistic fuzzy aggregation operators are proposed in this paper. We focus on comparisons with the existing power mean based intuitionistic fuzzy information aggregation approaches on numerical studies. Through comparative studies, we found some similarities between the operators proposed in this paper and the existing ones as well as a few differences. We use the proposed aggregation operators to multi-criteria decision making (MCDM) problem combined with IFNs. A real case about the job hunting problem of the contemporary college students is addressed based on the proposed method. The research of this paper indicates that the proposed MCDM is effective.