A Novel Probabilistic Linguistic Approach for Large-Scale Group Decision Making with Incomplete Weight Information

摘要: The large-scale group decision-making (GDM) problems with linguistic information have received more and attentions; however, how to effectively manage the assessments provided by large number of experts is still a challenge. In this paper, we employ probabilistic term sets (PLTSs), which are extension form hesitant fuzzy sets, assessments. We also present distance measure for PLTSs. To address GDM in weights groups completely unknown or partially known advance, develop method. First, propose consistency- consensus-based model objectively determine groups. Then, aggregate opinions all groups, new weighted arithmetic averaging operator using it collective assessment each alternative obtained. Finally, ranking alternatives obtained on basis dominance degrees optimal selected.