Multi-fidelity optimization via surrogate modelling
Alexander I. J. Forrester, András Sóbester, Andy J. Keane · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2007
This paper demonstrates the application of correlated Gaussian process based approximations to optimization where multiple levels of analysis are available, using an extension to the geostatistical method of co-kriging . An exchange algorithm is used to choose which points of the search space to sample within each level of analysis. The derivation of the co-kriging equations is presented in an intuitive manner, along with a new variance estimator to account for varying degrees of computational ‘noise’ in the multiple levels of analysis. A multi-fidelity wing optimization is used to demonstrate the methodology.