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PIER PIER B PIER C PIER M PIER Letters
2012-01-12
Hybrid-Surrogate-Model-Based Efficient Global Optimization for High-Dimensional Antenna Design
By
Ling-Lu Chen,

    Dr. Ling-Lu Chen

    Institute of Electromagnetics

    Southwest Jiaotong University

    China

    Homepage

Cheng Liao,

    Dr. Cheng Liao

    Southwest Jiaotong University

    China

    Homepage

Wenbin Lin,

    Dr. Wenbin Lin

    Southwest Jiaotong University

    China

    Homepage

Lei Chang,

    Dr. Lei Chang

    No. 36 Research Institute of CETC

    China

    Homepage

Xuan-Ming Zhong

    Dr. Xuan-Ming Zhong

    Institute of Electromagnetics

    Southwest Jiaotong University

    China

    Homepage

Progress In Electromagnetics Research, Vol. 124, 85-100, 2012
doi:10.2528/PIER11121203
Abstract
Efficient global optimization has been extensively used in problems with expensive cost functions. However, this method is not suitable for high-dimensional problems. In this paper, the radial basis function network is introduced into the efficient global optimization, to avoid local optima and achieve a fast convergence for high-dimensional optimization. Our algorithm is applied to a 12-dimensional optimization of a transmitting antenna. Compared to the genetic-algorithm-based efficient global optimization and the differential evolution strategy, our algorithm converges to the global optimal value more efficiently.
Citation
Ling-Lu Chen, Cheng Liao, Wenbin Lin, Lei Chang, and Xuan-Ming Zhong, "Hybrid-Surrogate-Model-Based Efficient Global Optimization for High-Dimensional Antenna Design," Progress In Electromagnetics Research, Vol. 124, 85-100, 2012.
doi:10.2528/PIER11121203
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