Approximating DEX Utility Functions with Methods UTA and ACUTA

Abstract

DEX is a qualitative multi-criteria decision analysis (MCDA) method, aimed at supporting decision makers in evaluating and choosing decision alternatives. We present results of a preliminary study in which we experimentally assessed the performance of two wellknown MCDA methods UTA and ACUTA to approximate qualitative DEX utility functions with piecewise-linear marginal utility functions. This is seen as a way to improve the sensitivity of qualitative models and provide a better insight in DEX utility functions. The results indicate that the approach is in principle feasible, but at this stage suffers from problems of convergence, insufficient sensitivity and inappropriate handling of symmetric functions.