A Dual Kriging Approach With Improved Points Selection Algorithm for Memory Efficient Surrogate Optimization in Electromagnetics

摘要

This paper introduces a new approach to kriging surrogate model sampling points allocation. By introducing the second (dual) kriging during the model construction, the existing sampling points are reallocated to reduce overall memory requirements. Moreover, a new algorithm is proposed for selecting the position of the next sampling point by utilizing a modified expected improvement criterion.