Comparison of different hybridization strategies in evolutionary optimization for EM

Author

Grimaccia, F. ; Mussetta, M. ; Zich, R.E.

Author_Institution

Dipt. di Elettrotecnica, Politecnico di Milano

fYear

2006

fDate

9-14 July 2006

Firstpage

585

Lastpage

588

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

Keywords

antenna theory; genetic algorithms; linear antenna arrays; particle swarm optimisation; EM structures; electromagnetic structures; evolutionary approaches; evolutionary optimization; genetic algorithm; genetical swarm optimization; hybridization strategies; linear array antenna; particle swarm optimization; Algorithm design and analysis; Convergence; Cultural differences; Design optimization; Evolutionary computation; Genetic algorithms; Heuristic algorithms; Linear antenna arrays; Particle swarm optimization; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation Society International Symposium 2006, IEEE

Conference_Location

Albuquerque, NM

Print_ISBN

1-4244-0123-2

Type

conf

DOI

10.1109/APS.2006.1710591

Filename

1710591