Binary particle swarm optimization of FSS using a CG-FFT modelling

During the last years, several approaches that combine heuristic optimization methods with numerical analysis techniques have been proposed in the literature to carry out the optimization of frequency selective surfaces (FSS) under frequency, periodicity and/or geometry restrictions. In this work, a procedure that combines a binary particle swarm optimization algorithm (BPSO) with a rigorous numerical method, the conjugate gradient fast Fourier transform (CG-FFT), is presented and applied to carry out the optimization of the FSS unit cell geometry subject to a frequency response stated in terms of masks for both transmission and reflection coefficients. Up to eight BPSO-based schemes have been considered for the optimization algorithm. Representative results comparing the BPSO schemes are included and discussed.