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Comparison of a Real-Coding Genetic Algorithm and Particle Swarm Optimization on a Band Gap Bandwidth Maximization Problem

Lukáš Oliva, Viktor Otevřel, Zbyněk Raida. Comparison of a Real-Coding Genetic Algorithm and Particle Swarm Optimization on a Band Gap Bandwidth Maximization Problem. In proceedings of Microcoll 2007. Budapest: Budapest University of Technology and Economics, 2007. 131 p.
Type
conference paper
Language
English
Authors
Oliva Lukáš, Ing., UREL (FEEC)
Otevřel Viktor, Ing., Ph.D.
Raida Zbyněk, prof. Dr. Ing., UREL (FEEC)
Abstract

In this paper, two global optimization algorithms, particle swarm optimization (PSO) and mean-adaptive real-coding genetic algorithm (MAD-RCGA) are applied to a problem of optimizing non-traditional dielectric electromagnetic band gap structures (EBG). The problem is formulated in nine dimensions with the goal of finding as large frequency gap between the first and the second TM bands as possible. Maximizing the frequency gap enables to improve properties of planar patch antennas in wide band.

Keywords

Global optimization, Real-coding genetic algorithm, Particle swarm optimization.

Published
2007
Pages
131
Proceedings
proceedings of Microcoll 2007
Conference
12th International Conference Microcoll 2007
Publisher
Budapest University of Technology and Economics
Place
Budapest
BibTeX 
@inproceedings{BUT22358,
  author="Lukáš {Oliva} and Viktor {Otevřel} and Zbyněk {Raida}",
  title="Comparison of a Real-Coding Genetic Algorithm and Particle Swarm Optimization on a Band Gap Bandwidth Maximization Problem",
  booktitle="proceedings of Microcoll 2007",
  year="2007",
  pages="131",
  publisher="Budapest University of Technology and Economics",
  address="Budapest"
}
Departments
Department of Radio Electronics (UREL)
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