Abstract:

Aiming at the risky group decision making problem with a stochastic variable and unknown weight, two models of combining decision maker’s and expert’s subject probability are presented based on Bayesian theory, according to whether the decision maker has prior information and whether the expert’s deviation is known. With those multivariate Bayesian aggregation models, a consensus probability distribution of each criterion’s value is attained first. Then, by means of Monte Carlo simulation, a rank probability exception index is calculated which represents the probability of different ranks an alternative might get. Finally, an exception ranking score is defined as well, which can aid a decision maker to choose the best alternative. The solution procedure is given and the effectiveness of this approach is showed by an example.