Inferring robust decision models in multicriteria classification problems: an experimental analysisInferring robust decision models in multicriteria classification problems: an experimental analysis Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2015-11-092014enRecent research on robust decision aiding has focused on identifying a range of recommendations from preferential information and the selection of representative models compatible with preferential constraints. This study presents an experimental analysis on the relationship between the results of a single decision model (additive value function) and the ones from the full set of compatible models in classification problems. Different optimization formulations for selecting a representative model are tested on artificially generated data sets with varying characteristics.http://creativecommons.org/licenses/by/4.0/European Journal of Operational Research2362601-611 Michael Doumpos Δουμπος Μιχαλης Zopounidis Konstantinos Ζοπουνιδης Κωνσταντινος Galariotis, Emilios Elsevier Multiple criteria analysis Robustness Disaggregation analysis Monte Carlo simulation