EM-driven multi-objective optimization of antenna structures in multi-dimensional design spaces

Feasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing nondominated solutions is identified beforehand using a novel Pareto-ranking based algorithm. The designs obtained by MOEA are subsequently obtained through response correction techniques. Our approach is demonstrated using a planar Yagi antenna.