Optimization of a reflectarray antenna via hybrid evolutionary algorithms

In this paper a new effective optimization algorithm called genetical swarm optimization (GSO) will be presented. It has been developed in order to combine in the most effective way the properties of two of the most popular evolutionary optimization approaches now in use for the optimization of electromagnetic structures, the particle swarm optimization (PSO) and genetic algorithms (GA). This algorithm is essentially a population-based heuristic search technique, which can be used to solve combinatorial optimization problems, modeled on the concepts of natural selection and evolution (GA) but also based on cultural and social rules derived from the analysis of the swarm intelligence and from the interaction among particles (PSO). The algorithm is tested here with respect to the other optimization techniques dealing with the optimal design of an elliptical reflectarray antenna with printed elements and an off-set feed

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