Moving Least Square-Based Hybrid Genetic Algorithm for Optimal Design of -Band Dual-Reflector Antenna

In this paper, we propose a hybrid genetic algorithm (GA) for the optimal shape design of an axially symmetric dual-reflector antenna by combining the GA with the moving least square (MLS), which enhances the convergence rate and the global search performance. The MLS is used to construct local inte...

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Bibliographic Details
Published in:IEEE transactions on magnetics 2019-06, Vol.55 (6), p.1-4
Main Authors: Lee, Kang-In, Oh, Hyun-Su, Jung, Sang-Hoon, Chung, Young-Seek
Format: Article
Language:English
Subjects:
Convergence
Dual-reflector antennas (DRAs)
Genetic algorithms
genetic algorithms (GAs)
Interpolation
Least squares
Magnetism
moving least square (MLS)
Optimization
Reflector antennas
Shape
Signal processing algorithms
Sociology
Statistics
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Summary:In this paper, we propose a hybrid genetic algorithm (GA) for the optimal shape design of an axially symmetric dual-reflector antenna by combining the GA with the moving least square (MLS), which enhances the convergence rate and the global search performance. The MLS is used to construct local interpolation functions from non-uniform sample data and to estimate new superior positions. By combining these superior positions in the next generation, the MLS-GA shows better search performance for the global optimum and a faster convergence rate than those of the conventional GA. To verify the proposed MLS-GA, we applied it to the optimal shape design of the DRA at the W-band.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2019.2895068