Intuitionistic fuzzy information aggregation and its application on multi-criteria decision-making

Abstract

As for many practical evaluation problems, the experts are asked to provide the information not only about the evaluation results of the research objects but also the familiarity with the research topics (belief levels). The goal of this paper is to investigate the intuitionistic fuzzy information aggregation methods under belief levels. First, I briefly recall the basic concepts of intuitionistic fuzzy sets. Then, I propose some generalized belief aggregation operators to aggregate the intuitionistic fuzzy values, such as the generalized belief intuitionistic fuzzy weighted averaging operator and the generalized belief intuitionistic fuzzy ordered weighted averaging operator. Then again, I research the properties and special cases of the proposed operators. Last, a real example about the anonymous review of National Science Foundation of China is employed to show the effectiveness of the proposed method in practical applications.

Confidence levelsq‐rung orthopair fuzzy aggregation operators and its applications to MCDM problems

“…Next, Zhao and Wei proposed the intuitionistic fuzzy Einstein hybrid geometric operator and intuitionistic fuzzy Einstein hybrid averaging operator on the basis of Einstein sum and Einstein product. Many practitioners such as Xu Tan and Chen, Xia et al, Xia and Xu, Yu, Cagman and Karatas, Yu, Ma and Zeng, Delia and Cagman, Joshi and Kharayat, and so on, have investigated the MCDM problems under the different aspects of intuitionistic fuzzy environments. Furthermore, a comprehensive study of intuitionistic fuzzy aggregation operators to solve MCDM problem has been compiled by Yu and Xu and Zhao …”