In this article, a new generalized iterative technique is presented for finding the approximate solution of a system of linear equations $ Ax = b $. The efficiency of iterative technique is analyzed by implementing it on some examples, and then comparing with existing methods. A parameter introduced in the method plays very vital role for a better and rapid solution. Convergence analysis is also examined. Findings of this paper may stimulate further research in this area.
Citation: Kamsing Nonlaopon, Farooq Ahmed Shah, Khaleel Ahmed, Ghulam Farid. A generalized iterative scheme with computational results concerning the systems of linear equations[J]. AIMS Mathematics, 2023, 8(3): 6504-6519. doi: 10.3934/math.2023328
In this article, a new generalized iterative technique is presented for finding the approximate solution of a system of linear equations $ Ax = b $. The efficiency of iterative technique is analyzed by implementing it on some examples, and then comparing with existing methods. A parameter introduced in the method plays very vital role for a better and rapid solution. Convergence analysis is also examined. Findings of this paper may stimulate further research in this area.
[1] | G. Cramer, Introduction a l'analyse des lignes courbes algébriques, A Geneva: Fréres Cramer and Cl. Philibert, 1730. |
[2] | R. L. Burden, J. D. Faires, Numerical analysis, Boston: PWS, 1980. |
[3] | Y. Saad, Iterative methods for sparse linear systems, SIAM, 2003. https://doi.org/10.1137/1.9780898718003 |
[4] | D. K. Salkuyeh, Generalized Jacobi and Gauss-Seidel methods for solving linear system of equations, Numer. Math. J. Chin. Univ., 16 (2007), 164–170. |
[5] | R. S. Varga, Iterative analysis, Berlin: Springer, 1962. |
[6] | D. M. Young, Iterative Solution of Large Linear Systems, Elsevier, 2014. |
[7] | C. E. Froberg, Numerical Mathematics: Theory and computer applications, Basic Books, 1985. |
[8] | A. Hadjidimos, Accelerated overrelaxation method, Math. Comput., 32 (1978), 149–157. http://doi.org/10.2307/2006264 doi: 10.2307/2006264 |
[9] | G. Avdelas, A. Hadjidimos, A. Yeyios, Some theoretical and computational results concerning the accelerated overrelaxation (AOR) method, Math. Rev. Anal. Numér. Théor. Approximation, 9 (1980), 5–10. |
[10] | A. I. Faruk, A. Ndanusa, Improvements of successive overrelaxation iterative (SOR) method for L-matrices, SJBAS, 1 (2020), 218–223. |
[11] | Z. Mayaki, A. Ndanusa, Modified successive overrelaxation (SOR) type methods for M-matrices, Sci. World J., 14 (2019), 1–5. |
[12] | K. Audu, Y. Yahaya, K. Adeboye, U. Abubakar, A. Ndanusa, Triple accelerated over-relaxation method for system of linear equations, Int. J. Math. Educ. Sci. Technol., 16 (2020), 137–146. |
[13] | Z. Z. Bai, The monotone convergence rate of the parallel nonlinear AOR method, Comput. Math. Appl., 31 (1996), 1–8. https://doi.org/10.1016/0898-1221(96)00013-2 doi: 10.1016/0898-1221(96)00013-2 |
[14] | Z. Z. Bai, Asynchronous multisplitting AOR methods for a class of systems of weakly nonlinear equations, Appl. Math. Comput., 98 (1999), 49–59. https://doi.org/10.1016/S0096-3003(97)10154-0 doi: 10.1016/S0096-3003(97)10154-0 |
[15] | R. Ali, I. Khan, A. Ali, A. Mohamed, Two new generalized iteration methods for solving absolute value equations using m-matrix, AIMS Mathematics, 7 (2022), 8176–8187. https://doi.org/10.3934/math.2022455 doi: 10.3934/math.2022455 |
[16] | L. Cvetkovic, V. Kostic, A note on the convergence of the AOR method, Appl. Math. Comput., 194 (2007), 394–399. https://doi.org/10.1016/j.amc.2007.04.030 doi: 10.1016/j.amc.2007.04.030 |
[17] | M. Fallah, S. Edalatpanah, On the some new preconditioned generalized AOR methods for solving weighted linear least squares problems, IEEE, 8 (2020), 33196–33201. https://doi.org/10.1007/s40314-016-0350-8 doi: 10.1007/s40314-016-0350-8 |
[18] | Z. X. Gao, T. Z. Huang, Convergence of AOR method, Appl. Math. Comput., 176 (2006), 134–140. https://doi.org/10.1016/j.amc.2005.09.020 |
[19] | F. Hailu, G. G. Gonfa, H. M. Chemeda, Second degree generalized successive over relaxation method for solving system of linear equations, MEJS, 2 (2020), 60–71. https://doi.org/10.4314/mejs.v12i1.4 doi: 10.4314/mejs.v12i1.4 |
[20] | V. Kumar Vatti, G. Chinna Rao, S. S. Pai, Parametric Accelerated Over Relaxation (PAOR) method, Adv. Intell. Syst. Comput., 979 (2020), 283–288. https://doi.org/10.1007/978-981-15-3215-3-27 doi: 10.1007/978-981-15-3215-3-27 |
[21] | W. Li, W. Sun, Comparison results for parallel multisplitting methods with applications to AOR methods, Linear Algebra Appl., 331 (2001), 131–144. https://doi.org/10.1016/S0024-3795(01)00276-2 doi: 10.1016/S0024-3795(01)00276-2 |
[22] | A. Yeyios, A necessary condition for the convergence of the accelerated overrelaxation (AOR) method, J. Comput. Appl. Math., 26 (1989), 371–373. https://doi.org/10.1016/0377-0427(89)90309-9 doi: 10.1016/0377-0427(89)90309-9 |
[23] | J. Y. Yuan, X. Q. Jin, Convergence of the generalized AOR method, Appl. Math. Comput., 99 (1999), 35–46. https://doi.org/10.1016/S0096-3003(97)10175-8 doi: 10.1016/S0096-3003(97)10175-8 |
[24] | Y. T. Li, C. X. Li, S. L. Wu, Improvements of preconditioned AOR iterative method for L-matrices, J. Comput. Appl. Math., 206 (2007), 656–665. https://doi.org/10.1016/j.cam.2006.08.019 doi: 10.1016/j.cam.2006.08.019 |
[25] | Y. T. Li, C. X. Li, S. L. Wu, Improving AOR method for consistent linear systems, Appl. Math. Comput., 186 (2007), 379–388. https://doi.org/10.1016/j.amc.2006.07.097 doi: 10.1016/j.amc.2006.07.097 |
[26] | Z. Q. Wang, Optimization of the parameterized Uzawa preconditioners for saddle point matrices, J. Comput. Appl. Math., 226 (2009), 136–154. https://doi.org/10.1016/j.cam.2008.05.019 doi: 10.1016/j.cam.2008.05.019 |
[27] | M. Wu, L. Wang, Y. Song, Preconditioned AOR iterative method for linear systems, Appl. Numer. Math., 57 (2007), 672–685. https://doi.org/10.1016/j.apnum.2006.07.029 doi: 10.1016/j.apnum.2006.07.029 |
[28] | S. Wu, T. Huang, A modified AOR-type iterative method for L-matrix linear systems, ANZIAM, 49 (2007), 281–292. https://doi.org/10.1017/S1446181100012840 doi: 10.1017/S1446181100012840 |
[29] | J. H. Yun, Comparison results of the preconditioned AOR methods for L-matrices, Appl. Math. Comput., 218 (2011), 3399–3413. https://doi.org/10.1016/j.amc.2011.08.085 doi: 10.1016/j.amc.2011.08.085 |
[30] | J. W. Pearson, J. Pestana, Preconditioners for Krylov subspace methods: An overview, GAMM-Mitt., 43 (2020), e202000015. https://doi.org/10.1002/gamm.202000015 doi: 10.1002/gamm.202000015 |
[31] | Z. Z. Bai, Sharp error bounds of some Krylov subspace methods for non-Hermitian linear systems, Appl. Math. Comput., 109 (2000), 273–285. |
[32] | R. Kehl, R. Nabben, D. B. Szyld, Adaptive multilevel Krylov methods, Electron. Trans. Numer. Anal., 51 (2019). |
[33] | E. Kreyszig, Introductory Functional analysis with applications, Wiley, 1991. |
[34] | M. Darivishi, The best values of parameters in accelerated successive overrelaxation methods, WSEAS Trans. Math., 3 (2004), 505–510. |
[35] | M. A. Noor, J. Iqbal, K. I. Noor, E. Al-Said, On an iterative method for solving absolute value equations, Optim. Lett., 6 (2012), 1027–1033. https://doi.org/10.1007/s11590-011-0332-0 doi: 10.1007/s11590-011-0332-0 |
[36] | M. A. Noor, K. I. Noor, M. Waseem, A new decomposition technique for solving a system of linear equations, J. Assoc. Arab Univ. Basic Appl. Sci., 16 (2014), 27–33. http://doi.org/10.1016/j.jaubas.2013.07.001 doi: 10.1016/j.jaubas.2013.07.001 |