Managing Model Fidelity for Efficient Optimization of Antennas using Variable-resolution Electromagnetic Simulations

Electromagnetic (EM) simulation has become an important tool in the design of contemporary antenna structures. However, accurate simulations of realistic antenna models are expensive and therefore design automation by employing EM solver within an optimization loop may be prohibitive because of its high computational cost. Efficient EM-driven antenna design can be performed using surrogate-based optimization (SBO). A generic approach to construct surrogate models of antennas involves the use of coarse-discretization EM simulations (low-fidelity models). A proper selection of the surrogate model fidelity is a key factor that influences both the performance of the design optimization process and its computational cost. Despite its importance, this issue has not yet been investigated in the literature. Here, we focus on a problem of proper surrogate model management. More specifically, we carry out a numerical study that aims at finding a trade-off between the design cost and reliability of the SBO algorithms. Our considerations are illustrated using several antenna design cases. Furthermore, we demonstrate that the use of multiple models of different fidelity may be beneficial to reduce the design cost while maintaining the robustness of the optimization process.