On the Local Behavior of an Interior Point Method for
Nonlinear Programming
R. Byrd, G. Liu and J. Nocedal
We study the local convergence of a primal-dual interior point
method for nonlinear programming. A linearly convergent version
of this algorithm has been shown in an earlier paper to be capable
of solving large and difficult non-convex problems. But for the
algorithm to reach its full potential, it must converge rapidly
to the solution. In this paper we describe how to design the algorithm
so that it converges superlinearly on regular problems.
Report OTC 98/02, Optimization Technology Center,
January 1998.
(To appear in the Proceedings of the 1997 Dundee Conference
on Numerical Analysis)
Contact: [email protected]