Now showing items 1-3 of 3
On the Superlinear and Quadratic Convergence of Primal-Dual Interior Point Linear Programming Algorithms
This paper presents a convergence rate analysis for interior point primal-dual linear programming algorithms. Conditions that guarantee Q-superlinear convergence are identified in two distinct theories. Both state that, ...
On the Superlinear Convergence of Interior Point Algorithms for a General Class of Problems
In this paper, we extend the Q-superlinear convergence theory recently developed by Zhang, Tapia and Dennis for a class of interior point linear programming algorithms to similar interior point algorithms for quadratic ...
The Mehrotra Predictor-Corrector Interior-Point Method as a Perturbed Composite Newton Method
The simplified Newton method reduces the work required by Newton's method per iteration by reusing the initial Jacobian matrix. However, fast convergence is sacrificed. The level-m composite Newton method attempts to balance ...