An indicator for the switch from derivative-free to derivative-based optimization

In some optimization problems found in applications, the derivatives of the objective function can be computed or approximated but at an expensive cost, and it is desirable to know when to use derivative-free methods (such as direct search, for instance) or derivative-based methods (such as gradient or quasi-Newton methods). Derivative-free methods may achieve a steady initial progress for some problems, but after some advance they may also become slower or even stagnate due to the lack of derivatives. It is thus of interest to provide a way to appropriately switch from a derivative-free method to a derivative-based one. In this paper, we develop a family of indicators for such a switch based on the decrease properties of both classes of methods (typically used when deriving worst case complexity bounds).