CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThis study analyzes the influence of sparse matrix reordering on the solution of linear systems arising from interior point methods for linear programming. In particular, such linear systems are solved by the conjugate gradient method with a two-phase hybrid preconditioner that uses the controlled Cholesky factorization during the initial iterations and later adopts the splitting preconditioner. This approach yields satisfactory computational results for the solution of linear systems with symmetric positive-definite matrices. Three reordering heuristics are analyzed in this study: the reverse Cuthill-McKee heuris...
Recent advances in linear programming solution methodology have focused on interior point algorithms...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse ...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse...
This article presents improvements to the hybrid preconditioner previously developed for the solutio...
In this work, iterative methods are used to solve the linear systems of equations arising from inter...
The computational burden of primal-dual interior point methods for linear program-ming relies on the...
CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PE...
This article presents improvements to the hybrid preconditioner previously developed for the solutio...
Interior point methods usually rely on iterative methods to solve the linear systems of large scale ...
A new class of preconditioners for the iterative solution of the linear systems arising from interio...
We devise a hybrid approach for solving linear systems arising from interior point methods applied t...
AbstractA new class of preconditioners for the iterative solution of the linear systems arising from...
We propose an adaptation of the Feasible Direction Interior Points Algorithm (FDIPA) of J. Herskovit...
. In this paper, we discuss efficient implementation of a new class of preconditioners for linear sy...
A new class of preconditioners for the iterative solution of the linear systems arising from interio...
Recent advances in linear programming solution methodology have focused on interior point algorithms...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse ...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse...
This article presents improvements to the hybrid preconditioner previously developed for the solutio...
In this work, iterative methods are used to solve the linear systems of equations arising from inter...
The computational burden of primal-dual interior point methods for linear program-ming relies on the...
CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PE...
This article presents improvements to the hybrid preconditioner previously developed for the solutio...
Interior point methods usually rely on iterative methods to solve the linear systems of large scale ...
A new class of preconditioners for the iterative solution of the linear systems arising from interio...
We devise a hybrid approach for solving linear systems arising from interior point methods applied t...
AbstractA new class of preconditioners for the iterative solution of the linear systems arising from...
We propose an adaptation of the Feasible Direction Interior Points Algorithm (FDIPA) of J. Herskovit...
. In this paper, we discuss efficient implementation of a new class of preconditioners for linear sy...
A new class of preconditioners for the iterative solution of the linear systems arising from interio...
Recent advances in linear programming solution methodology have focused on interior point algorithms...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse ...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse...