A Dynamic Evolutionary Algorithm for Automated Antenna Design

2012 ◽  
Vol 9 (2) ◽  
pp. 243-248
Author(s):  
Sanyou Zeng ◽  
Huanhuan Li ◽  
Zhengjun Li ◽  
Hongyong Jing ◽  
Wei Dong
Keyword(s):  
Evolutionary Algorithm ◽  
Antenna Design ◽  
Automated Antenna Design

Antenna design using dynamic multi‐objective evolutionary algorithm

2018 ◽  
Vol 12 (13) ◽  
pp. 2065-2072 ◽  
Author(s):  
Ruwang Jiao ◽  
Yongzhi Sun ◽  
Jianqing Sun ◽  
Yuhong Jiang ◽  
Sanyou Zeng
Keyword(s):  
Evolutionary Algorithm ◽  
Antenna Design ◽  
Multi Objective

Tools for Automated Antenna Design and Optimization

2007 ◽  
Vol 4 (5) ◽  
pp. 853-864 ◽  
Author(s):  
Jason Lohn ◽  
Gregory Hornby ◽  
Derek Linden
Keyword(s):  
Antenna Design ◽  
Design And Optimization ◽  
Automated Antenna Design

An Evolutionary Algorithm and Its Application in Antenna Design

2012 ◽  
Vol 1 (2) ◽  
pp. 129-137 ◽  
Author(s):  
Sanyou Zeng ◽  
Zhu Liu ◽  
Changhe Li ◽  
Qing Zhang ◽  
Weiguang Wang
Keyword(s):  
Evolutionary Algorithm ◽  
Antenna Design

scholarly journals Optimization of a Conical Corrugated Antenna Using Multiobjective Heuristics for Radio-Astronomy Applications

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
S. López-Ruiz ◽  
R. Sánchez Montero ◽  
F. Tercero-Martínez ◽  
P. L. López-Espí ◽  
J. A. López-Fernandez
Keyword(s):  
Particle Swarm Optimization ◽  
Evolutionary Algorithm ◽  
Radio Astronomy ◽  
Particle Swarm ◽  
Horn Antenna ◽  
Pso Algorithm ◽  
Antenna Design ◽  
Swarm Optimization ◽  
Linear Profile ◽  
Corrugated Horn

This paper presents the design of a tree sections corrugated horn antenna with a modified linear profile, using NURBS, suitable for radio-astronomy applications. The operating band ranges from 4.5 to 8.8 GHz. The aperture efficiency is higher than 84% and the return losses are greater than 20 dB in the whole bandwidth. The antenna optimization has been carried out with multiobjective versions of an evolutionary algorithm (EA) and a particle swarm optimization (PSO) algorithm. We show that both techniques provide good antenna design, but the experience carried out shows that the results of the evolutionary algorithm outperform the particle swarm results.

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