A technique for low-cost multiobjective optimization of antennas in highly dimensional parameter spaces is presented. The optimization procedure is expedited by exploiting fast surrogate models, including coarse-discretization electromagnetic (EM) antenna simulations and response surface approximations (RSA). The latter is utilized to yield an initial set of Pareto nondominated designs that are further refined using response correction methods. Efficient handling of multiple geometry parameters is realized by the initial reduction of the solution space. Our approach is demonstrated using a 13-parameter triple trapezoidal, planar ultrawideband (UWB) monopole antenna.
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Kozieł et al. (2014) studied this question.
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