Obtaining Quadratic Models of Noisy Functions
When derivatives of a nonlinear objective function are unavailable, many derivative- free optimization algorithms rely on interpolation-based models of the function. But what if the function values are contaminated by noise, as in most of the simulation- based problems typically encountered in this area? We propose to obtain linear and quadratic models by using knowledge … Read more