Optimization of a reflectarray antenna via hybrid evolutionary algorithms

被引：4
|
作者：
Grimaccia, F. [1 ]
Mussetta, M. [1 ]
Pirinoli, P. [2 ]
Zich, R. E. [1 ]
机构：
[1] Politecn Milan, Dipartimento Elettrotecn, Piazza Leonardo da Vinci 32, I-20133 Milan, Italy
[2] Politecn Torino, Departimento Electron, I-10129 Turin, Italy
来源：
2006 17TH INTERNATIONAL ZURICH SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY, VOLS 1 AND 2 | 2006年
关键词：
D O I：
10.1109/EMCZUR.2006.214918
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：254 / +
页数：2
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