| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1032671 | Omega | 2013 | 9 Pages |
We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers' preferences, and imprecise weights are represented by trapezoidal fuzzy weights. The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights.An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure.
► We consider incomplete information within multi-attribute utility theory. ► Imprecise weights are represented by trapezoidal fuzzy weights. ► A dominance intensity measure is used to rank the alternatives under consideration. ► We use distances based on the generalization of the left and right fuzzy numbers. ► The performance of the method is analyzed by using MonteCarlo simulation.
