Convergence Analysis of Inexact Infeasible-Interior-Point Algorithms for Solving Linear Programming Problems

Authors:
Janos Korzak
Affiliations:
-
Venue:
SIAM Journal on Optimization
Year:
2000

Citing 0
Cited 3

Convergence Analysis of an Inexact Infeasible Interior Point Method for Semidefinite Programming

Computational Optimization and Applications
An iterative solver-based long-step infeasible primal-dual path-following algorithm for convex QP based on a class of preconditioners

Optimization Methods & Software
Matrix-free interior point method

Computational Optimization and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present a convergence analysis for some inexact (polynomial) variants of the infeasible-interior-point algorithm of Kojima, Megiddo, and Mizuno. For this analysis we assume that the iterates are bounded. The new variants allow the use of search directions that are calculated from the defining linear system with only moderate accuracy, e.g., via the use of Krylov subspace methods like CG or QMR. Furthermore, some numerical results for the proposed methods are given.