Dynamic stochastic multi-criteria decision making method based on cumulative prospect theory and set pair analysis

A method based on cumulative prospect theory and set pair analysis is proposed for dynamic stochastic multi-criteria decision making problems, in which the information about criteria weight is completely unknown and criteria values are in the form of discrete random variables. Decision-maker's attitude towards risk is introduced into this paper. Firstly, the prospect value of alternatives is calculated on all criteria at different periods according to distribution function. Secondly, the time series weight is derived based on the binomial distribution probability density function. The criteria weight is ascertained by the algorithm of maximizing deviation. Then, the concepts of identity degree, contrary degree, set pair potential are employed and thus the order of alternatives can be determined consequently. Finally, an example of risk investment illustrates the effectiveness of this method.