Social network (SN) provides a new perspective for large-scale multi-attribute group decision making (LMAGDM), and the scale and complexity of group compositions have received considerable attention. In recent study, the SN is constructed artificially and subjectively by using the number of communication or by giving the trust value directly. This paper constructs a directed and weighted SN by integrating collaboration network and reference network of decision makers (DMs) objectively. The spin-glass of community detection method is used to identify the subgroups and the weight of DMs in subgroups and then obtain the weight of subgroup pair. The uncertain linguistic weighted average operator is used to represent each subgroup’s assessment. The closeness between two subgroups is defined to measure consensus level. A targeted local feedback mechanism with three identification rules and a recommendation rule is designed to guide the consensus reaching process (CRP) more precisely and effectively. An illustrative example proves the feasibility and validity of the proposed consensus method, and the comparative analysis highlights the advantages and characteristics of this model.
ABSTRACT
PUBLICATION RECORD
- Publication year
2019
- Venue
Journal of Intelligent & Fuzzy Systems
- Publication date
2019-08-07
- Fields of study
Mathematics, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar
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