An Improved Iterative Scheme using Successive Over-relaxation for Solution of Linear System of Equations
Improved SOR for Linear Systems of Equations
DOI:
https://doi.org/10.53560/PPASA(59-3)653Keywords:
GSOR, RGSOR, Diagonally Dominant, Irreducibly Diagonally Dominant, Rate of ConvergenceAbstract
To solve the system of linear equations is one of the hottest topics in iterative methods. The system of linear equations occurs in business, engineering, social and in sensitive research areas like medicine, therefore applying efficient matrix solvers to such systems is crucial. In this paper, an improved iterative scheme using successive overrelaxation has been constructed. The proposed iterative method converges well when a linear system’s matrix is M-matrix, Symmetric positive definite with some conditions, irreducibly diagonally dominant, strictly diagonally dominant, and H-matrix. Such type of linear system of equations does arise usually from ordinary differential equations and partial differential equations. The improved iterative scheme has decreased spectral radius, improved stability and reduced the number of iterations. To show the effectiveness of the improved scheme, it is compared with the refinement of generalized successive over-relaxation and generalized successive over-relaxation method with the help of numerical experiments using MATLAB software.
References
H. Muleta, and G. Gofe. Refinement of generalized accelerated over relaxation method for solving system of linear equations based on the Nekrassov-Mehmke1-method. Ethiopian Journal of Education and Sciences 13: 1-18 (2018).
Y. Saad. Iterative methods for sparse linear systems. Society for Industrial and Applied Mathematics USA (2003).
V.K. Vatti, and G.G. Gonfa. Refinement of generalized Jacobi (RGJ) method for solving system of linear equations. International Journal of Contemporary Mathematical Sciences 6: 109-116 (2011).
F. Mohammed, and M. Rivaie. Jacobi–Davidson, Gauss–Seidel and successive over-relaxation for solving systems of linear equations. Applied Mathematics and Computational Intelligence 6: 41-52 (2017).
F. Hailu, G.G. Gonfa, and H.M. Chemeda. Second Degree Generalized Successive Over Relaxation Method for Solving System of Linear Equations. Momona Ethiopian Journal of Science 12: 60-71 (2020).
M. Saha, and J. Chakrabarty. On generalized jacobi, gauss-seidel and SOR methods. arXiv, Cornell University 1806.07682 (2018).
G.G. Gonfa. Refined Iterative Method for Solving System of Linear Equations. American Journal of Computational and Applied Mathematics 6: 144–47 (2016).
R.A. Horn, and C. R. Johnson. Matrix Analysis. Cambridge University Press, Cambridge, England MR0832183 (1985).
B.N. Datta. Numerical Linear Algebra and Applications. Society for Industrial and Applied Mathematics, Philadelphia, USA (2010).
R.L. Burden, and J.D. Faires. Numerical Analysis. Cengage Learning (2015).
M.S.R. Baloch, Z.A. Kalhoro, M.S. Khalil, and A.W. Shaikh. A New Improved Classical Iterative Algorithm for Solving System of Linear Equations. Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences 58: 69-81 (2021).
G. Dessalew, T. Kebede, G. Awgichew, and A. Walelign. Generalized Refinement of Gauss-Seidel Method for Consistently Ordered 2-Cyclic Matrices.Abstract and Applied Analysis 2021: 8343207 (2021).