Algorithms for Bound Constrained Quadratic Programing Problems.

摘要

We present an algorithm which combines standard active set strategies with the gradient projection method for the solution of quadratic programming problems subject to bounds. We show, in particular, that if the quadratic is bounded below on the feasible set then termination occurs at a stationary point in a finite number of iterations. Moreover, if all stationary points are nondegenerate, termination occurs at a local minimizer. A numerical comparison of the algorithm based on the gradient projection algorithm with a standard active set strategy shows that on mildly degenerate problems the gradient projection algorithm requires considerably less iterations typically decreasing by at least a factor of 10. For strongly degenerate problems, the performance of the gradient projection algorithms deteriorates, but it still performs better than the active set method. 25 refs., 1 fig., 15 tabs. (ERA citation 13:055964)