Probability Scoring and Uncertainty Modeling in Multi-Criteria Decision Analysis

Multi-Criteria Decision Analysis (MCDA) problems very often involve mul-tiple Decision Makers (DMs). In this paper, we present several new decision analysis algorithms to consider both subjective decision criteria and objec-tive decision criteria with different treatment of their uncertainty. The un-certainty and availability of weight for decision criteria are also studied, and probability scoring is developed to score the criteria. Finally, a case study is presented