In this thesis we will present an effective method for solving systems of linear equations with large sparse matrices using LU factorization. The goal is to avoid filling the matrix by non-zero entries during the computations. Firstly we dis- cuss the use of permutations for the matrix algorithms. Afterwards we present the maximum matching algorithm and Tarjan's algorithm, both based on graph theory. Tarjan's algorithm is used to achieve block triangular form and the max- imum matching gives us the permutation into a matrix with zero free diagonal, which is recommended as a precursor to Tarjan's algorithm.
We present a new method for the a priori approximation of the orders of magnitude of the entries in ...
Abstract. This paper generalizes to the nonlinear case a standard way to solve general sparse system...
The objective of this work is to compare the developed LU factorization update with results from MIN...
We consider the problem of permuting the rows and columns of a rectangular or square, unsymmetric sp...
AbstractA new sparse approximate triangular factorization technique for solving large sparse linear ...
Abstract. Variants of the p4 algorithm of Hellerman and Rarick and the p5 algorithm of Erisman, Grim...
This work investigates the problem of permuting a sparse rectangular matrix into block diagonal form...
Abstract- This paper presents a new approach for the solution of Linear Programming Problems with th...
AbstractIn this work, the solution of a large sparse linear system of equations with an arbitrary sp...
In solving large sparse linear least squares problems $Ax \cong b$, several different numeric metho...
A lot of technical problems lead to systems of linear equations. The matrices of the systems are oft...
AbstractWe describe a set of procedures for computing and updating an LU factorization of a sparse m...
The solution of nearly square overdetermined linear systems is studied. The sparse QR technique is c...
KLU is a set of routines for solving sparse linear systems of equations. It is particularly well-sui...
AbstractIn this note we show that an asymptotically fast algorithm may be designed in order to reali...
We present a new method for the a priori approximation of the orders of magnitude of the entries in ...
Abstract. This paper generalizes to the nonlinear case a standard way to solve general sparse system...
The objective of this work is to compare the developed LU factorization update with results from MIN...
We consider the problem of permuting the rows and columns of a rectangular or square, unsymmetric sp...
AbstractA new sparse approximate triangular factorization technique for solving large sparse linear ...
Abstract. Variants of the p4 algorithm of Hellerman and Rarick and the p5 algorithm of Erisman, Grim...
This work investigates the problem of permuting a sparse rectangular matrix into block diagonal form...
Abstract- This paper presents a new approach for the solution of Linear Programming Problems with th...
AbstractIn this work, the solution of a large sparse linear system of equations with an arbitrary sp...
In solving large sparse linear least squares problems $Ax \cong b$, several different numeric metho...
A lot of technical problems lead to systems of linear equations. The matrices of the systems are oft...
AbstractWe describe a set of procedures for computing and updating an LU factorization of a sparse m...
The solution of nearly square overdetermined linear systems is studied. The sparse QR technique is c...
KLU is a set of routines for solving sparse linear systems of equations. It is particularly well-sui...
AbstractIn this note we show that an asymptotically fast algorithm may be designed in order to reali...
We present a new method for the a priori approximation of the orders of magnitude of the entries in ...
Abstract. This paper generalizes to the nonlinear case a standard way to solve general sparse system...
The objective of this work is to compare the developed LU factorization update with results from MIN...