Original scientific paper

Genetical Swarm Optimization: an Evolutionary Algorithm for Antenna Design

Alessandro Gandelli
Francesco Grimaccia
Marco Mussetta
Paola Pirinoli
Riccardo Enrico Zich

Abstract

In this paper a new effective optimization algorithm called Genetical Swarm Optimization (GSO) is presented. This is an hybrid algorithm 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, as PSO and GA, 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). Preliminary analyses are here presented with respect to the other optimization techniques dealing with a classical optimization problem. The optimized design of a printed reflectarray antenna is finally reported with numerical results.

Keywords

evolutionary optimization; hybridization strategies; reflectarray antennas

Hrčak ID:

9143

URI

https://hrcak.srce.hr/9143

Publication date:

6.12.2006.

Article data in other languages: croatian

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