Groupe d’études et de recherche en analyse des décisions

# Surrogate models for derivative-free optimization

In an optimization process that requires many evaluations of a time-consuming function $$f$$, it can be interesting to build a surrogate model of f, which is a simplified and more time-efficient version of this function. The surrogate model uses the known value of $$f$$ on a set of training points to estimate this function anywhere on its definition space.