This paper concerns the use of iterative solvers in interior point methods for linear and quadratic programming problems. We state an adaptive termination rule for the inner iterative scheme and we prove the global convergence of the obtained algorithm, exploiting the theory developed for inexact Newton methods. This approach is promising for problems with special structure on parallel computers. We present an application on Cray T3E/256 and SGI Origin 2000/64 arising in stochastic linear programming and robust optimization, where the constraint matrix is block-angular and extremely large
5siIn this article, we address the efficient numerical solution of linear and quadratic programming ...
Due to the structure of the solution set, an exact solution to a linear program cannot be computed b...
Optimization problems with many more inequality constraints than variables arise in support-vector m...
In this paper, we describe a variant of the Newton Interior{Point method in [8] for nonlinear progra...
In the first part of this research we consider a linesearch globalization of the local primal-dual i...
Abstract. Solution methods for very large scale optimization problems are addressed in this paper. I...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/1...
This paper deals with the solution of nonlinear programming problems arising from elliptic control p...
An algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based o...
In this paper, we present an interior-point algorithm for large and sparse convex quadratic programm...
We present a parallel interior point algorithm to solve block structured linear programs. This algor...
This paper deals with the solution of nonlinear programming problems arising from elliptic control p...
We report the results obtained by a parallel Interior-Point method combined with the Preconditioned ...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
5siIn this article, we address the efficient numerical solution of linear and quadratic programming ...
Due to the structure of the solution set, an exact solution to a linear program cannot be computed b...
Optimization problems with many more inequality constraints than variables arise in support-vector m...
In this paper, we describe a variant of the Newton Interior{Point method in [8] for nonlinear progra...
In the first part of this research we consider a linesearch globalization of the local primal-dual i...
Abstract. Solution methods for very large scale optimization problems are addressed in this paper. I...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/1...
This paper deals with the solution of nonlinear programming problems arising from elliptic control p...
An algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based o...
In this paper, we present an interior-point algorithm for large and sparse convex quadratic programm...
We present a parallel interior point algorithm to solve block structured linear programs. This algor...
This paper deals with the solution of nonlinear programming problems arising from elliptic control p...
We report the results obtained by a parallel Interior-Point method combined with the Preconditioned ...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
5siIn this article, we address the efficient numerical solution of linear and quadratic programming ...
Due to the structure of the solution set, an exact solution to a linear program cannot be computed b...
Optimization problems with many more inequality constraints than variables arise in support-vector m...