An Optimization Framework Using Sequential Approximation Model and Multimodal Evolution Strategy

This paper presents an optimization methodology which employs a Kriging model together with a restricted evolution strategy (ES). The global and local optima are obtained using the restricted ES. Of these optima, some points are selected to enter the sample data set and the Kriging model is reconstructed using the updated sample data set. The numerical tests show that the proposed method is quite efficient for a surrogate-assisted optimization framework