  In this paper, we extend the idea of using controlled perturbations to
enhance the capabilities of active-set prediction for interior point methods
for convex Quadratic Programming (QP) problems. Namely, we consider perturbing
the inequality constraints (by a small amount) so as to enlarge the feasible
set. We show that if the perturbations are chosen judiciously, then there
exists a primal-dual pair of points which is close to the optimal solution of
the perturbed problems and the corresponding active and inactive sets at this
point are the same as the optimal active and inactive sets at an optimal
solution of the original QP problems. Additionally, we prove that the optimal
tripartition of the original problems can also be predicted by solving the
perturbed ones. Furthermore, encouraging preliminary numerical experience is
also presented for the QP case.
