volume | PIER Journals

Abstract

Taguchi method has been extensively applied in electromagnetic optimization. To further enhance the optimization efficiency of the Taguchi method, a surrogate-assisted Taguchi method employing dynamic reduced rates is proposed. The reduced rate of each design variable is proportional to its contribution percentage. Variables with higher contributions exhibit a larger reduction rate, which subsequently decreases the search step and enhances the exploitation and convergence of the Taguchi method. The Kriging model serves as a substitute for the real fitness evaluation in predicting the result of each experiment, with its feasible state determined by the average relative error of its predictions. This ensures the prediction accuracy while reducing the number of real fitness evaluations. The proposed algorithm is validated by the fact that the efficiency has increased at least twofold through four benchmark function tests. In the end, this algorithm is employed to synthesize the radiation pattern of an asymmetrical dipole array with 16 elements and to optimize the front-to-back ratio of the Yagi-Uda antenna.

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Dr. Jianing Ma

Dr. Xingning Jia

Dr. Ruidong Wang

Dr. Liao Ma