Accelerated multiobjective design of miniaturized microwave components by means of nested kriging surrogates

Design of microwave components is an inherently multiobjective task. Often, the objectives are at least partially conflicting and the designer has to work out a suitable compromise. In practice, generating the best possible trade-off designs requires multiobjective optimization, which is a computationally demanding task. If the structure of interest is evaluated through full-wave electromagnetic (EM) analysis, the employment of widely used population-based metaheuristics algorithms may become prohibitive in computational terms. This is a common situation for miniaturized components, where considerable cross-coupling effects make traditional representations (eg, network equivalents) grossly inaccurate. This article presents a framework for accelerated EM-driven multiobjective design of compact microwave devices. It adopts a recently reported nested kriging methodology to identify the parameter space region containing the Pareto front and to render a fast surrogate, subsequently used to find the first approximation of the Pareto set. The final trade-off designs are produced in a separate, surrogate-assisted refinement process. Our approach is demonstrated using a three-section impedance matching transformer designed for the best matching and the minimum footprint area. The Pareto set is generated at the cost of only a few hundred of high-fidelity EM simulations of the transformer circuit despite a large number of geometry parameters involved.