Abstract

The genetical swarm optimization (GSO) is the integration of the genetic algorithm (GA) and particle swarm optimization (PSO). The key feature of this algorithm is that it maintains the integration of GA and PSO for the entire run. In this paper the authors present a comparison of the GSO and different hybridization strategies, in order to explore in the most effective way the properties of the evolutionary approaches now in use for the optimization of EM structures, and to validate the performances of their hybrid procedure. Some results of the tested algorithm are shown in the design optimization of a linear array antenna.

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