  The types of constraints encountered in black-box and simulation-based
optimization problems differ significantly from those treated in nonlinear
programming. We introduce a characterization of constraints to address this
situation. We provide formal definitions for several constraint classes and
present illustrative examples in the context of the resulting taxonomy. This
taxonomy, denoted QRAK, is useful for modeling and problem formulation, as well
as optimization software development and deployment. It can also be used as the
basis for a dialog with practitioners in moving problems to increasingly
solvable branches of optimization.
