A method for the incorporation of parametric uncertainty in the weighted evaluation multi-attribute decision analysis model

We develop an extension of the classic Weighted Evaluation (WE) Multi-Attribute Decision Analysis (MADA) model that allows for uncertainty in the parameters of the model. Uncertainties in attribute importance weights and alternative evaluation ratings are represented by independent uniform, triangular or beta random variables; and an iterative multi-variate integration scheme is used to evaluate the mean, variance and skewness of the resulting Probabilistic Weighted Evaluation (PWE).