Abstract Through the two-tuple linguistic aggregation method based on the Steiner point, the evaluation information is quantified into the coordinate point set in the corresponding two-dimensional coordinate system through the correlation transformation rules. The Steiner point (the optimal aggregation point of expert population, namely the consensus point of the population) of the corresponding interval point set is obtained by using the plant simulated growth algorithm. According to the inverse mapping relationship, this study presents a new approach to group decision making problems with interval two-tuple linguistic based on social network analysis and experts’ confidence preference. The subjective weight of experts was adjusted by combining experts’ confidence coefficient and influence in social network structure, and the objective weight was obtained by combining experts’ relative importance coefficient and group similarity coefficient. Finally, the comprehensive weight of experts was determined, and the schemes were prioritized. An example is given to illustrate the feasibility and effectiveness of the method.
ZONG Mengting,ZONG Menghuan,CHEN Xi1. Research on a Method of Interval Two-Tuple Linguistic Group Decision-Making Based on Social Network Analysis[J]. Chinese Journal of Management, 2022, 19(1): 74-.
