Class GaussSeidelSolver

java.lang.Object
org.ojalgo.matrix.task.iterative.IterativeSolverTask
org.ojalgo.matrix.task.iterative.GaussSeidelSolver
All Implemented Interfaces:
MatrixTask<Double>, SolverTask<Double>
public final class GaussSeidelSolver extends IterativeSolverTask
Stationary Gauss–Seidel iteration for solving [A][x]=[b] with non-zero diagonal entries.

Convergence

  • Converges for strictly diagonally dominant systems and for symmetric positive-definite (SPD) matrices.
  • Behaviour depends on ordering and scaling; preconditioning is not applied in this stationary method.
Configuration
  • Ignores any configured Preconditioner; use the relaxation factor to control convergence speed.

When to use

  • As a simple in-place fixed-point iteration when sequential updates are acceptable.
  • Prefer over fully synchronous updates when in-place coupling improves convergence.
  • For large SPD problems needing faster convergence, Krylov methods often perform better.
  • If fully synchronous updates or trivial parallelism are required, consider a synchronous fixed-point method.