"Visualization of Choquet Integrals, OWA operators, Input values and Fuzzy measures"

Abstract

Interval UTA method has been proposed as an intermediate model between the conventional UTA and UTA-GMS methods. It can be seen as a semi-robust ordinal regression method providing a safer evaluation than the conventional UTA method with a less computation than UTA-GMS method. We found that the preference relation obtained from the identified interval model does not match well to the preference probability between alternatives obtained by a Monte Carlo simulation. We improve the identification method so as to match more to the preference probability by replacing the objective function of the identification problem with another one. We confirm that proposed method is improved by numerical experiments.