An Efficient Direct Search Methodology for Robust Optimization of Electromagnetic Devices

A direct search formulation to treat the robust performances as additional constrained functions is proposed for robust optimization of electromagnetic devices under uncertainties. To solve the resulting robust optimization problem, a robust-oriented quantum-inspired evolutionary algorithm (QEA) is proposed. In the proposed robust-oriented QEA, a mechanism to activate the robust performance checking procedure only to promising solution is introduced, and an automatic updating mechanism for the increment angle is designed to guarantee a good balance between exploration and exploitation searches. Also, the stochastic approximation method is employed to minimize the computational burdens in determining the gradient information. The numerical results on two case studies are reported in order to validate the feasibility and the merit of the proposed direct search methodology in solving both benchmark problems and practical engineering robust optimal designs.