A novel incomplete hesitant fuzzy information supplement and clustering method for large-scale group decision-making.

ABSTRACT: Clustering is an effective means to reduce the scaling of large-scale group decision-making (LSGDM). However, there are many problems with clustering methods, such as incomplete or ambiguous information usually provided by different decision makers. Traditional clustering methods may not be able to handle these situations effectively, resulting in incomplete decision-making information. Calculating the clustering centers may become very complex and time-consuming. Inappropriate distance weights may also lead to incorrect cluster assignments, and these problems will seriously affect the clustering results. This research provides a novel incomplete hesitant fuzzy information supplement and clustering approach for large-scale group decision-making in order to address the aforementioned diffic

SUBMITTER: Wang J 

PROVIDER: S-EPMC10807752 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature