We present a new, external, active constraints set strategy for solving nonlinear programming problems with a large number of inequality constraints that arise in the process of discretizing continuous-time optimal control problems with state-space constraints. This strategy constructs a sequence of inequality constrained nonlinear programming problems, containing a progressively larger subset of the constraints in the original problem, and submits them to a nonlinear programming solver for a fixed number of iterations. We prove that this scheme computes a solution of the original problem and show by means of numerical experiments that this strategy results in reductions in computing time ranging from a factor of 6 to a factor of over 100.