CUT: a multicriteria approach for concavifiable preferences ArgyrisNikolaos MortonAlec FigueiraJose Rui 2016 We consider the problem of helping a decision maker (DM) choose from a set of multiattributed objects when her preferences are "concavifiable," i.e. representable by a concave value function. We establish conditions under which preferences or preference intensities are concavifiable. We also derive a characterization for the family of concave value functions compatible with a set of such preference statements expressed by the DM. This can be used to validate dominance relations over discrete sets of alternatives and forms the basis of an interactive procedure. We report on the practical use of this procedure with several DMs for a flat-choice problem and its computational performance on a set of project-portfolio selection problem instances. The use of preference intensities is found to provide significant improvements to the performance of the procedure.