  Intrinsic noise in objective function and derivatives evaluations may cause
premature termination of optimization algorithms. Evaluation complexity bounds
taking this situation into account are presented in the framework of a
deterministic trust-region method. The results show that the presence of
intrinsic noise may dominate these bounds, in contrast with what is known for
methods in which the inexactness in function and derivatives' evaluations is
fully controllable. Moreover, the new analysis provides estimates of the
optimality level achievable, should noise cause early termination. It finally
sheds some light on the impact of inexact computer arithmetic on evaluation
complexity.
