Simulation of fuzzy multiattribute models for grey relationships
Multiattribute decision making involves tradeoffs among alternative performances over multiple attributes. The accuracy of performance measures are usually assumed to be accurate. Most multiattribute models also assume given values for the relative importance of weights for attributes. However, there is usually some uncertainty involved in both of these model inputs. Outranking multiattribute methods have always provided fuzzy input for performance scores. Many analysts have also recognized that weight estimates also involve some imprecision, either through individual decision maker uncertainty, or through aggregation of diverging group member preferences. Many fuzzy multiattribute models have been proposed, but they have focused on identifying the expected value solution (or extreme solutions). This paper demonstrates how simulation can be used to reflect fuzzy inputs, which allows more complete probabilistic interpretation of model results.
multiple attribute decision making (madm) fuzzy sets monte carlo simulation grey analysis