  The Lipschitz constant of a response surface function upper bounds the
sensitivity of a dependent variable to changes in the independent ones.
Traditionally, such constants have found much implicit and abstract use in
mathematically oriented applications, but their potential for explicit use in
more engineering-based domains has not been explored. The latter point is the
subject of this paper, where we propose several ways in which the Lipschitz
constants may be used explicitly in the domain of experimental optimization.
Specifically, we focus on how they may help ensure the satisfaction of
constraints and on their potential role in reducing the negative effects of
measurement or estimation uncertainty. A number of refinements to the proposed
approaches are also derived, and some techniques for setting the constants are
presented.
