scholarly journals Automated Antenna Design with Evolutionary Algorithms

Space 2006 ◽  
2006 ◽  
Author(s):  
Gregory Hornby ◽  
Al Globus ◽  
Derek Linden ◽  
Jason Lohn
2011 ◽  
Vol 19 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Gregory. S. Hornby ◽  
Jason D. Lohn ◽  
Derek S. Linden

Whereas the current practice of designing antennas by hand is severely limited because it is both time and labor intensive and requires a significant amount of domain knowledge, evolutionary algorithms can be used to search the design space and automatically find novel antenna designs that are more effective than would otherwise be developed. Here we present our work in using evolutionary algorithms to automatically design an X-band antenna for NASA's Space Technology 5 (ST5) spacecraft. Two evolutionary algorithms were used: the first uses a vector of real-valued parameters and the second uses a tree-structured generative representation for constructing the antenna. The highest-performance antennas from both algorithms were fabricated and tested and both outperformed a hand-designed antenna produced by the antenna contractor for the mission. Subsequent changes to the spacecraft orbit resulted in a change in requirements for the spacecraft antenna. By adjusting our fitness function we were able to rapidly evolve a new set of antennas for this mission in less than a month. One of these new antenna designs was built, tested, and approved for deployment on the three ST5 spacecraft, which were successfully launched into space on March 22, 2006. This evolved antenna design is the first computer-evolved antenna to be deployed for any application and is the first computer-evolved hardware in space.


2007 ◽  
Vol 4 (5) ◽  
pp. 853-864 ◽  
Author(s):  
Jason Lohn ◽  
Gregory Hornby ◽  
Derek Linden

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

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Sotirios K. Goudos ◽  
Christos Kalialakis ◽  
Raj Mittra

A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is presented. EAs have emerged as viable candidates for global optimization problems and have been attracting the attention of the research community interested in solving real-world engineering problems, as evidenced by the fact that very large number of antenna design problems have been addressed in the literature in recent years by using EAs. In this paper, our primary focus is on Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), and Differential Evolution (DE), though we also briefly review other recently introduced nature-inspired algorithms. An overview of case examples optimized by each family of algorithms is included in the paper.


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