An intuitionistic linguistic MCDM model based on probabilistic exceedance method and evidence theory

The optimization in multi-criteria decision making under uncertain conditions has attracted more and more scholars in recent years. However, it is still an open issue that how to better evaluate the satisfaction with more complex objects. Since the great performance of intuitionistic fuzzy set on handling the uncertain information, in this paper, a new fuzzy linguistic model for non-scalar criteria satisfaction expressed via intuitionistic fuzzy sets is proposed, which makes experts evaluate more objectively. Moreover, a corresponding aggregation approach based on the Choquet probabilistic exceedance method is also proposed. After a series of calculation processes, the final aggregated results embodied by intuitionistic fuzzy sets (IFSs) can be obtained. Then by converting them into the belief intervals, the best alternative can be selected more objectively. In addition, two real-life applications are shown to demonstrate the practicality of proposed method.