An Influence Network-Based Consensus Model for Large-Scale Group Decision Making with Linguistic Information

Abstract The vast majority of the existing social network-based group decision-making models require extra information such as trust/distrust, influence and so on. However, in practical process, it is difficult to get additional apart from opinions decision makers. For large-scale making (LSGDM) problem which makers articulate their preferences form comparative linguistic expressions, this paper proposes a consensus model based on an network inferred directly preference information. First, modified agglomerative hierarchical clustering algorithm developed detect subgroups LSGDM with flexible Meanwhile, measure method level proposed optimal can be determined. Second, according members, constructed by determining intra-cluster inter-cluster relationships. Third, two-stage feedback mechanism guided established for reaching adopts cluster adjustment strategy individual depending different levels consensus. not only effectively improve efficiency LSGDM, but also take into account. Finally, feasibility effectiveness are verified case intelligent environmental protection project location decision.