A MADM Alternative Ranking Approach under Uncertainty

The individual preferences for gains, losses, and uncertain events, which are first proposed by prospect theory, are rarely considered in current MADM methods. To solve this problem, a MADM alternative ranking approach under uncertainty is presented. The presented approach proposes a method for eliciting individual preferences for gains, losses and uncertain events by using the trade off method and the certainty equivalent method, based on which, the individual overall utilities of alternatives on each attribute are determined by incorporating the utilities of gains and losses with their corresponding decision weightings of uncertain events, and finally alternatives are ranked by using swing weighting method to balance relative dominances of attributes. By comparing with other approaches on a simulation example, the presented approach is proved to be scientific, reasonable, and well applicable to MADM alternative rankings under uncertainty.