Multi-attribute group decision-making under probabilistic uncertain linguistic environment
提出概率不确定语言术语集概念，研究其规范化、比较、运算和聚合算子，并开发两种多属性群决策方法，用于云存储服务选择等场景。
Existing decision-making methods cannot work under the probabilistic uncertain linguistic environment where the decision makers give different uncertain linguistic terms as their assessments and the weights of assessments are different. In this paper, a novel concept called probabilistic uncertain linguistic term set is proposed, which is composed of some possible uncertain linguistic terms associated with the corresponding probabilities. Then, the normalization process, comparison method, basic operations, and aggregation operators are studied for probabilistic uncertain linguistic term sets. After that, an extended technique for order preference by similarity to an ideal solution method and an aggregation-based method are developed to rank the alternatives and then select the best one for multi-attribute group decision-making with probabilistic uncertain linguistic information. Finally, a practical case concerning the selection of Cloud storage services is shown to illustrate the applicability of probabilistic uncertain linguistic term sets.