Abstract
Traditional large-scale group decision-making (LSGDM) methods assume that the decision-makers (DMs) are independent, and the trust relationships among DMs in the social network (SN) are complete. However, DMs always influence each other, and practical trust relationships among DMs in the SN are often incomplete. In this study, we propose a picture fuzzy LSGDM approach in a trust-relationship-based SN environment to solve decision-making problems. To achieve this, the incomplete trust relationship of SNs was considered first and the missing information was estimated using a picture fuzzy trust propagation operator. Next, a novel picture fuzzy Jensen a-norm dissimilarity measure was defined and the corresponding consensus detection model was developed for LSGDM in a trust-relationship-based SN environment. Afterward, based on the technique for order of preference by similarity to ideal solution (TOPSIS) approach, a picture fuzzy dissimilarity-based selection method was proposed for the selection process. Finally, two case studies were provided to demonstrate the effectiveness of the proposed approach. The sensitivity and comparison analyses demonstrated the stability and reliability of the decision-making results obtained using this method.
Original language | English |
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Journal | Information Sciences |
Volume | 608 |
Early online date | 20 Jul 2022 |
DOIs | |
Publication status | Published - 31 Aug 2022 |
Keywords
- large-scale group decision-making
- trust-relationship-based social network
- picture fuzzy numbers
- dissimilarity measure
- TOPSIS