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I'm working on a project, implementing Successive over-relaxation (SOR) method (http://en.wikipedia.org/wiki/Successive_over-relaxation) using Python. SOR can only apply if given matrix is,

  • symmetric positive-definite (SPD) OR
  • strictly or irreducibly diagonally dominant.

I want to know how to calculate the relaxation factor(ω) for faster convergence.

  • Is there a BEST value for ω ?
  • If exists, how to calculate it?
  • Any suggestions are also welcome.

Thank you in advance.

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See this scicomp.SE question and this article – J. M. Jul 14 '12 at 14:56
@J.M. your "this article" link (dx.doi.org/10.1093/comjnl/9.2.200) doesn't work. – Sajith Janaprasad Jul 14 '12 at 15:04
Hmm, odd. Try this. – J. M. Jul 14 '12 at 15:07

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