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2010-11-10

A Hybrid Optimized Algorithm Based on Ego and Taguchi's Method for Solving Expensive Evaluation Problems of Antenna Design

By Nan Sheng, Cheng Liao, Wenbin Lin, Lei Chang, Qinghong Zhang, and Haijing Zhou
Progress In Electromagnetics Research C, Vol. 17, 181-192, 2010
doi:10.2528/PIERC10091303

Abstract

In this paper, we propose a hybrid optimization approach that combines the Efficient Global Optimization (EGO) algorithm with Taguchi's method. This hybrid optimized algorithm is suited for problems with expensive cost functions. As a Bayesian analysis optimization algorithm, EGO algorithm begins with fitting the Kriging model with n sample points, and finds the (n+1)th point where the expected improvement is maximized to update the model. We employ Taguchi's method in EGO to obtain the (n+1)th point in this paper. A numerical simulation demonstrates that our algorithm has advantage over the original EGO. Finally, we apply this hybrid optimized algorithm to optimize an ultra-wide band (UWB) transverse electromagnetic (TEM) horn antenna and a linear antenna array. Compared to Taguchi's method and the Integer Coded Differential Evolution Strategy, our algorithm converges to the global optimal value more efficiently.

Citation


Nan Sheng, Cheng Liao, Wenbin Lin, Lei Chang, Qinghong Zhang, and Haijing Zhou, "A Hybrid Optimized Algorithm Based on Ego and Taguchi's Method for Solving Expensive Evaluation Problems of Antenna Design," Progress In Electromagnetics Research C, Vol. 17, 181-192, 2010.
doi:10.2528/PIERC10091303
http://jpier.org/PIERC/pier.php?paper=10091303

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