Development and Validation of Different Hybridization Strategies to Explore GSO Performances

An effective optimization algorithm suitably developed for antenna design applications is here presented in various hybrid forms. With respect to this hybrid approach, called GSO, a validation campaign has been conducted following different strategies, in order to combine in the most effective way the properties of two of the most popular evolutionary optimization approaches now in use for optimization of electromagnetic structures, the particle swarm optimization and genetic algorithms. The algorithm effectiveness has been tested for various benchmark problems as a first step, analyzing different computational costs, and finally some numerical results are reported for an EM application, the optimization of a linear array.