  The computationally-efficient solution of multi-objective optimization
problems (MOPs) arising in the design of modern electromagnetic (EM) microwave
devices is addressed. Towards this end, a novel System-by-Design (SbD) method
is developed to effectively explore the solution space and to provide the
decision maker with a set of optimal trade-off solutions minimizing multiple
and (generally) contrasting objectives. The proposed MO-SbD method proves a
high computational efficiency, with a remarkable time saving with respect to a
competitive state-of-the-art MOP solution strategy, thanks to the "smart"
integration of evolutionary-inspired concepts and operators with artificial
intelligence (AI) and machine learning (ML) techniques. Representative
numerical results are reported to provide the interested users with useful
insights and guidelines on the proposed optimization method as well as to
assess its effectiveness in designing mm-wave automotive radar antennas.
