Large-Scale Group Decision-Making Method Using Hesitant Fuzzy Rule-Based Network for Asset Allocation

Abstract

Large-scale group decision-making (LSGDM) has become common in the new era of technology development involving a large number of experts. Recently, in the use of social network analysis (SNA), the community detection method has been highlighted by researchers as a useful method in handling the complexity of LSGDM. However, it is still challenging to deal with the reliability and hesitancy of information as well as the interpretability of the method. For this reason, we introduce a new approach of a Z-hesitant fuzzy network with the community detection method being put into practice for stock selection. The proposed approach was subsequently compared to an established approach in order to evaluate its applicability and efficacy.

Keywords

• alternatives selection
• large scale
• networked rule-based
• fuzzy sets
• Z-numbers
• community detection method