A Criteria Weighting Method: Intuitionistic Fuzzy Network Method (IFNM)

The complex multi-criteria group decision-making (MCGDM) problems contain numerous criteria, which require multiple experts to compare the importance of criteria to determine the criteria weights. However, owing to the limited knowledge and experience of experts, it is impossible for them to be knowledgeable about all criteria, which leads to giving incomplete judgments, namely, the important information of criteria contains missing values. To address the problem of criteria weighting under incomplete information in MCGDM, this paper proposes the intuitionistic fuzzy network approach, which is a new weighting method for determining the criteria weights. The core of the proposed weighting approach is to convert the incomplete rankings of the importance of criteria given by experts into a weighted criteria importance network, and the fuzzy dominance of the criteria is described using triangular intuitionistic fuzzy numbers (TIFNs). Finally, this paper applies the proposed weighting method to the effectiveness evaluation of unmanned aerial vehicle (UAV). Compared with the existing subjective weighting methods, the significant features of the proposed weighting method are:(1) it considers incomplete information; (2) it only requires n-1 comparisons; (3) it requires only the rankings of the importance of criteria, which eliminates the inconsistency of the expert’s preference in the judgment matrix-based methods; (4) the algorithm is simple, which is suitable for MCGDM problems with a large number of criteria.