= Nonlinear programming
{title2=$\min_x f(x)\text{ subject to }g_i(x)\le0,\ h_j(x)=0$}
{wiki}
= Nonlinear optimization
{synonym}
A <nonlinear programming> problem minimizes an objective over finitely many real variables subject to constraints, with at least one objective or constraint nonlinear. Parametrizing the pulse amplitudes in <quantum optimal control> produces such a problem. <Gradient descent> and related local methods exploit differentiability, but a local stationary point need not be a global optimum without additional convexity or other structure.
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