A new criterion for approximate designs called the standardized maximin criterion suited for both model discrimination and parameter estimation based on D- and D _s-optimality criteria is introduced and studied. It is proved that the computation of an experimental design which is optimal with respect to this criterion can be reduced to the computation of multiple experimental designs which are optimal with respect to the simpler weighted criterion. Several numerical examples that describe the efficiency of the proposed criterion are provided.