An outranking approach for multi-attribute group decision-making with interval-valued hesitant fuzzy information - Shen, Feng; Huang, Qinyuan; Su, Han; Xu, Zeshui (Engineering applications of artificial intelligence, 2024)
Multi-Attribute Group Decision-Making (MAGDM) problems have become more common, with interval-valued hesitant fuzzy set (IVHFS) being found to be suitable for describing some complex fuzzy information. This paper first determined the additional relationships between generalized interval-valued hesitant fuzzy weighted averaging (GIVHFWA) operators and generalized interval-valued hesitant fuzzy weighted geometric (GIVHFWG) operators, and proposed mean and variance for a sequence of interval-valued hesitant fuzzy elements (IVHFEs). This paper then developed an outranking approach for MAGDM based on these operators to solve a consensus selection problem. In the first stage, which was based on the k-means clustering method for IVHFEs with feedback strategy taking both local and global consensus into consideration and a new consensus measure derived from the proposed variance measure, a compromised consensus was determined for each group involved in the decision. In the second stage, which was based on a probabilistic interval-valued hesitant fuzzy outranking method, the optimal alternative was determined based on the consensus information from the first stage. A case study on the enterprise credit risk assessment was given to illustrate the viability of the proposed method, which was then also compared with other current methods to demonstrate its greater flexibility and potential value.