This work concerns the comparison of evolutionary algorithms and standard optimization methods on two circuit design problems: the parameter extraction of device circuit model and the multi-objective optimization of an Operational Transconductance Amplifier. We compare standard optimization techniques and evolutionary algorithms in terms of quality of the solutions and computational effort, that is, objective function evaluations needed to compute them. The experimental results obtained show as standard techniques are robust with respect evolutionary algorithms, while the latter are more effective in terms of the standard metrics and function calls. In particular for the multiobjective problem, the observed Pareto front determined by evolutionary algorithms has a better spread of solutions with a larger number of nondominated solutions with respect to the standard multi-objective techniques.