Similarity-Trust Network For Clustering Based Consensus Group Decision Making Model
Trust relation, as defined in Social Network Analysis(SNA), is one of the recent notions considered in de-cision making. This inspired our integration of trustrelation in constructing a similarity–trust network. Si-milarity of experts' preferences is analyzed inclusivelywith trust relation by defining a new combinationfunction of both attributes. The agglomerative hier-archical clustering approach is applied to group expertsinto subclusters based on the constructed similarity—trust degrees. The centrality concept from SNA is thenused to determine the expert's similarity–trust cen-trality (STC) index, which is the basis for the con-struction of a new aggregation operator, STC‐inducedordered weighted averaging operator, to fuse the in-dividual experts' preferences into a collective one, fromwhich the consensus solution is derived. An analysis ofresults with different levels of trust degree is carriedout. We show that this new idea is promising and re-levant to be used in solving certain consensus groupdecision‐making problems.
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
Citation : Ahlim, W.S.A.W., Kamis, N.H., Ahmad, S.A.S., Chiclana, F. (2021) Similarity-Trust Network For Clustering Based Consensus Group Decision Making Model. International Journal of Intelligent Systems.
ISSN : 0884-8173
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes