Title :
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
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;
Conference_Titel :
Antennas and Propagation Society International Symposium 2006, IEEE
Conference_Location :
Albuquerque, NM
Print_ISBN :
1-4244-0123-2
DOI :
10.1109/APS.2006.1710591
