%A Bin Xia
%A Minh Trien Pham
%A Ziyan Ren Ren
%A Yanli Zhang
%A Chang Seop Koh
%T Worst Case Scenario Robust Optimization Utilizing Adaptive Dynamic Taylor Kriging and Differential Evolution Algorithm
%X For the robust optimal design of electromagnetic problems under uncertainties, the robustness evaluation is the critical problem. This paper presents a surrogate model based worst case scenario optimization algorithm, where the adaptive dynamic Taylor Kriging is incorporated to construct a higher accurate surrogate model. Finally, an improved differential evo- lution algorithm, DE/λ-best/1/bin, is adopted to search for the global robust optimal solution.
%C Hangzhou, China
%D 2018
%L SisLab3252