Article ID: | iaor2004723 |
Country: | United States |
Volume: | 22 |
Issue: | 1 |
Start Page Number: | 1 |
End Page Number: | 42 |
Publication Date: | Feb 1997 |
Journal: | Mathematics of Operations Research |
Authors: | Todd M.J., Nesterov Y.E. |
This paper provides a theoretical foundation for efficient interior-point algorithms for convex programming problems expressed in conic form, when the cone and its associated barrier are self-scaled. For such problems we devise long-step and symmetric primal–dual methods. Because of the special properties of these cones and barriers, our algorithms can take steps that go typically a large fraction of the way to the boundary of the feasible region, rather than being confined to a ball of unit radius in the local norm defined by the Hessian of the barrier.