Full-wave Electromagnetic Optimizations Using Surface Integral Equations and the Multilevel Fast Multipole Algorithm

We present an electromagnetic optimization environment based on full-wave solutions via surface integral equations and the multilevel fast multipole algorithm (MLFMA). Optimizations are performed by using genetic algorithms, while the required trials are performed accurately via MLFMA. The developed mechanism can handle many different operations, such as portion moving/removing, rotation, and gap opening, that have different effects in the constructed matrix equations but that can efficiently be executed in numerical simulations. The effectiveness of the optimization environment is demonstrated on alternative problems, such as the design of pixel antennas and corrugated sheets for optimal electromagnetic responses.