Multi-objective design of UWB antennas using surrogate-based optimization

A procedure for multi-objective design of ultra-wideband (UWB) antennas is presented. The goal is to reduce the antenna size while ensuring that the matching requirements are satisfied. Our approach exploits the multi-objective evolutionary algorithm (MOEA) working with a fast surrogate model of the antenna obtained with kriging interpolation of coarse-discretization simulation data. Response correction techniques are subsequently applied to refine the designs obtained by MOEA. Our methodology allows us to obtain-at a low computational cost-a set of designs corresponding to various trade-offs between antenna size and matching.