The approaches for the parametric synthesis of the automatic control system (ACS) using the genetic algorithm that performs an approximation of Pareto-optimal solutions set are suggested. As a result, two approaches to multi-criteria optimization of ACS were considered: (1) the optimization problem was considered to be three-criteria for equally important criteria, (2) the optimization problem was considered to be two-criteria and a set of Pareto-optimal solutions was obtained for the main criteria. Then, for the final selection, a third criterion was additionally involved, the minimum value of which was sought within the Pareto-optimal set obtained by the main criteria. It is shown that the second approach is preferable to the first one, since it allows obtaining a reasonable solution in a shorter time and with less computational costs. This paper presents the results of multicriteria optimization of the system parameters obtained by MATLAB/Simulink and Global Optimization Toolbox.