Reducing the Pareto optimal set in MCDM using imprecise probabilities

An approach for reducing a set of Pareto optimal solutions on the basis of specific information about importance of criteria is proposed in the paper. The DM's judgments about criteria have a clear behaviour interpretation and can be used in various decision problems. It is shown that the imprecise probability theory can be successfully applied for formalising the available information which is represented by means of a set of probability measures. Simple explicit expressions instead of linear programming problems are derived for dealing with three decision rules: maximality, interval dominance and interval bound dominance rules. Numerical examples illustrate the proposed approach.