Abstract: We evaluate the performance of a numerical method
for global optimization of expensive functions. The method is using a
response surface to guide the search for the global optimum. This
metamodel could be based on radial basis functions, kriging, or a
combination of different models. We discuss how to set the cyclic
parameters of the optimization method to get a balance between local
and global search. We also discuss the eventual problem with Runge
oscillations in the response surface.