Comparison of different optimization techniques in antenna design - Part II

Author

Zich, R.E. ; Mussetta, M. ; Grimaccia, F. ; Banchetti, J. ; Guggiari, T. ; Catelan, A. Oregio ; Presti, F. Lo ; Testoni, O. ; Zanelli, T.

Author_Institution

Dipt. di Energia, Politec. di Milano, Milan, Italy

fYear

2012

fDate

8-14 July 2012

Firstpage

1

Lastpage

2

Abstract

In this paper an elliptical reflectarray antenna is optimized by some novel evolutionary techniques: Ant Colony Optimization (ACO), Biogeography Based Optimization (BBO), Differential Evolution (DE), Population-Based Incremental Learning (PBIL) and Stud Genetic Algorithm (SGA). The optimized design of the reflectarray is aimed to compare their performances on a complex EM optimization problem. Results show that some techniques (DE, BBO, SGA) are particularly effective in dealing with antenna optimization.

Keywords

ant colony optimisation; genetic algorithms; reflectarray antennas; ACO; BBO; DE; PBIL; SGA; ant colony optimization; antenna design; antenna optimization; biogeography based optimization; complex EM optimization problem; differential evolution; elliptical reflectarray antenna; evolutionary techniques; population-based incremental learning; stud genetic algorithm; Ant colony optimization; Apertures; Genetic algorithms; Optimization; Phased arrays; Reflector antennas;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation Society International Symposium (APSURSI), 2012 IEEE

Conference_Location

Chicago, IL

ISSN

1522-3965

Print_ISBN

978-1-4673-0461-0

Type

conf

DOI

10.1109/APS.2012.6348756

Filename

6348756