Dealing with degenerated cases in quadratic programming
Abstract
A new algorithm is described for quadratic programming which is based on a Cholesky factorization that uses a diagonal pivoting strategy and that allows to compute null or negative curvature directions. The algorithm is numerically stable and has shown efficiency solving positive-definite and indefinite problems. It is specially interesting in indefinite cases because the initial point does not need to be a vertex of the feasible set. So we avoid introducing artificial constraints in the problem, which turns out to be very efficient in parametric programming. At the same time techniques for updating matrix factorizations are used.