Surrogate-Assisted Enhanced Global Optimization Based on Hybrid DE for Antenna Design

A novel surrogate-assisted enhanced global optimization (SAEGO) method is proposed for antenna design. The proposed algorithm takes advantage of surrogate to improve efficiency of global optimization and combines global and local search to improve the accuracy of solution. The proposed algorithm is verified through optimization of Ackley function and a Yagi-Uda antenna. The results show that the proposed algorithm finds a more accurate minimum value with less computational time than other optimization algorithms.