Meta-optimization of bio-inspired algorithms for antenna array design

Virgilio Zúñiga-Grajeda; Alberto Coronado-Mendoza; Kelly Joel Gurubel-Tun

Kybernetika (2018)

  • Volume: 54, Issue: 3, page 610-628
  • ISSN: 0023-5954

Abstract

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In this article, a technique called Meta-Optimization is used to enhance the effectiveness of bio-inspired algorithms that solve antenna array synthesis problems. This technique consists on a second optimization layer that finds the best behavioral parameters for a given algorithm, which allows to achieve better results. Bio-inspired computational methods are useful to solve complex multidimensional problems such as the design of antenna arrays. However, their performance depends heavily on the initial parameters. In this paper, the distances between antenna array elements are calculated in order to reduce electromagnetic interference from undesired sources. The results are compared to previous works, showing an improvement on the performance of bio-inspired optimization algorithms such as Particle Swarm Optimization and Differential Evolution. These results are found to be statistically significant based on the Wilcoxon's rank sum test as compared to these methods using the standard parameters proposed in the literature. Furthermore, graphical representations of the Meta-Optimization process called meta-landscapes are presented, showing the behavior of these algorithms for a range of different parameters, providing the best parameter combinations for each antenna problem.

How to cite

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Zúñiga-Grajeda, Virgilio, Coronado-Mendoza, Alberto, and Gurubel-Tun, Kelly Joel. "Meta-optimization of bio-inspired algorithms for antenna array design." Kybernetika 54.3 (2018): 610-628. <http://eudml.org/doc/294758>.

@article{Zúñiga2018,
abstract = {In this article, a technique called Meta-Optimization is used to enhance the effectiveness of bio-inspired algorithms that solve antenna array synthesis problems. This technique consists on a second optimization layer that finds the best behavioral parameters for a given algorithm, which allows to achieve better results. Bio-inspired computational methods are useful to solve complex multidimensional problems such as the design of antenna arrays. However, their performance depends heavily on the initial parameters. In this paper, the distances between antenna array elements are calculated in order to reduce electromagnetic interference from undesired sources. The results are compared to previous works, showing an improvement on the performance of bio-inspired optimization algorithms such as Particle Swarm Optimization and Differential Evolution. These results are found to be statistically significant based on the Wilcoxon's rank sum test as compared to these methods using the standard parameters proposed in the literature. Furthermore, graphical representations of the Meta-Optimization process called meta-landscapes are presented, showing the behavior of these algorithms for a range of different parameters, providing the best parameter combinations for each antenna problem.},
author = {Zúñiga-Grajeda, Virgilio, Coronado-Mendoza, Alberto, Gurubel-Tun, Kelly Joel},
journal = {Kybernetika},
keywords = {bio-inspired algorithms; particle swarm optimization; differential evolution; meta-optimization; computer-aided design; antenna arrays},
language = {eng},
number = {3},
pages = {610-628},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Meta-optimization of bio-inspired algorithms for antenna array design},
url = {http://eudml.org/doc/294758},
volume = {54},
year = {2018},
}

TY - JOUR
AU - Zúñiga-Grajeda, Virgilio
AU - Coronado-Mendoza, Alberto
AU - Gurubel-Tun, Kelly Joel
TI - Meta-optimization of bio-inspired algorithms for antenna array design
JO - Kybernetika
PY - 2018
PB - Institute of Information Theory and Automation AS CR
VL - 54
IS - 3
SP - 610
EP - 628
AB - In this article, a technique called Meta-Optimization is used to enhance the effectiveness of bio-inspired algorithms that solve antenna array synthesis problems. This technique consists on a second optimization layer that finds the best behavioral parameters for a given algorithm, which allows to achieve better results. Bio-inspired computational methods are useful to solve complex multidimensional problems such as the design of antenna arrays. However, their performance depends heavily on the initial parameters. In this paper, the distances between antenna array elements are calculated in order to reduce electromagnetic interference from undesired sources. The results are compared to previous works, showing an improvement on the performance of bio-inspired optimization algorithms such as Particle Swarm Optimization and Differential Evolution. These results are found to be statistically significant based on the Wilcoxon's rank sum test as compared to these methods using the standard parameters proposed in the literature. Furthermore, graphical representations of the Meta-Optimization process called meta-landscapes are presented, showing the behavior of these algorithms for a range of different parameters, providing the best parameter combinations for each antenna problem.
LA - eng
KW - bio-inspired algorithms; particle swarm optimization; differential evolution; meta-optimization; computer-aided design; antenna arrays
UR - http://eudml.org/doc/294758
ER -

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