Abstract
This paper proposes the clustering procedure in group decision-making environments. We develop a fuzzy classification matrix according to the evaluation vectors gathered from each decision maker. Members of the group are clustered based on the nature of the classification matrix in which the presence of transitive law is verified. Without similarity relation, the power of the proposed matrix is introduced as a negotiation value among different ideas since it always holds the transitive nature. Then the group evaluation is finally obtained. Fuzzy classification matrix enables us to organize the evaluations of all the members at a time and to assess the similarity of participants effectively. Further, consistent clustering is mathematically realized due to the introduction of transitive law. This approach allows decision makers to conduct a reasonable group decision-making in the context of different objectives while integrating or adjusting diverse views and ideas.
