Research article

Generalization of the interval TOR method for solving interval linear systems

  • Received: 27 May 2025 Revised: 16 July 2025 Accepted: 28 July 2025 Published: 14 August 2025
  • MSC : 15A30, 65G30, 65G40, 65H10

  • Iterative methods for solving interval linear systems were presented in this paper. By generalizing interval diagonal matrices to interval band matrices, a generalization of the interval two-parameter overrelaxation method (GITOR) was introduced, and the convergence analysis of the proposed method was discussed. Specifically, if the coefficient matrices of the system are strictly diagonally dominant (SDD) matrices, interval M-matrices, or interval H-matrices, the proposed method converges under any initial approximation. Furthermore, an upper bound on the spectral radius of the iterative matrices was provided for interval strictly diagonally dominant matrices. Finally, numerical examples for each type of mentioned interval matrix were studied, demonstrating the efficiency of the proposed method.

    Citation: Lingjian Pu, Yan Zhu, Shiliang Wu. Generalization of the interval TOR method for solving interval linear systems[J]. AIMS Mathematics, 2025, 10(8): 18454-18474. doi: 10.3934/math.2025824

    Related Papers:

  • Iterative methods for solving interval linear systems were presented in this paper. By generalizing interval diagonal matrices to interval band matrices, a generalization of the interval two-parameter overrelaxation method (GITOR) was introduced, and the convergence analysis of the proposed method was discussed. Specifically, if the coefficient matrices of the system are strictly diagonally dominant (SDD) matrices, interval M-matrices, or interval H-matrices, the proposed method converges under any initial approximation. Furthermore, an upper bound on the spectral radius of the iterative matrices was provided for interval strictly diagonally dominant matrices. Finally, numerical examples for each type of mentioned interval matrix were studied, demonstrating the efficiency of the proposed method.



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    [1] G. Alefeld, J. Herzberger, Introduction to interval computation, Academic Press, 1983. https://doi.org/10.1016/C2009-0-21898-8
    [2] D. Wang, T. Li, P. Deng, Z. Luo, P. Zhang, K. Liu, et al., DNSRF: Deep network-based semi-NMF representation framework, ACM Trans. Intell. Syst. Technol., 15 (2024), 1–20. http://dx.doi.org/10.1145/3670408 doi: 10.1145/3670408
    [3] A. Neumaier, Interval methods for systems of equations, Cambridge University Press, 1991. https://doi.org/10.1017/CBO9780511526473
    [4] R. S. Varga, Matrix iterative analysis, Berlin, Heidelberg: Springer, 2000. https://doi.org/10.1007/978-3-642-05156-2
    [5] Q. R. Lian, Z. Y. Jin, K. Nickel, The SOR method for solving linear interval equations: A method for solving the eigenproblem of symmetric interval matrix, Inst. für Angew. Math., 87 (1987), 17–18.
    [6] M. Fiedler, J. Nedoma, J. Ramík, J. Rohn, K. Zimmermann, Linear optimization problems with inexact data, New York: Springer, 2006. https://doi.org/10.1007/0-387-32698-7
    [7] J. Chakravarty, A. Athikho, M. Saha, Convergence of interval AOR method for linear interval equations, Numer. Algebra Control Optim., 12 (2022), 293–308. http://dx.doi.org/10.3934/naco.2021006 doi: 10.3934/naco.2021006
    [8] A. Neumaier, A simple derivation of the Hansen-Bliek-Rohn-Ning-Kearfott enclosure for linear interval equations, Reliab. Comput., 5 (1999), 131–136. http://dx.doi.org/10.1023/A:1009997221089 doi: 10.1023/A:1009997221089
    [9] S. Ning, R. B. Kearfott, A comparison of some methods for solving linear interval equations, SIAM J. Numer. Anal., 34 (1997), 1289–1305. http://dx.doi.org/10.1137/s0036142994270995 doi: 10.1137/s0036142994270995
    [10] D. W. Chang, Convergence analysis of the parallel multisplitting TOR method, J. Comput. Appl. Math., 72 (1996), 169–177. http://dx.doi.org/10.1016/0377-0427(95)00270-7 doi: 10.1016/0377-0427(95)00270-7
    [11] D. W. Chang, The parallel multisplitting TOR (MTOR) method for linear systems, Comput. Math. Appl., 41 (2001), 215–227. http://dx.doi.org/10.1016/s0898-1221(01)85017-3 doi: 10.1016/s0898-1221(01)85017-3
    [12] J. Kuang, J. Ji, A survey of AOR and TOR methods, J. Comput. Appl. Math., 24 (1988), 3–12. http://dx.doi.org/10.1016/0377-0427(88)90340-8 doi: 10.1016/0377-0427(88)90340-8
    [13] L. T. Zhang, T. Z. Huang, S. H. Cheng, T. X. Gu, Y. P. Wang, A note on parallel multisplitting TOR method for H-matrices, Int. J. Comput. Math., 88 (2011), 501–507. http://dx.doi.org/10.1080/00207160903501917 doi: 10.1080/00207160903501917
    [14] M. Hladik, I. Skalna, Relations between various methods for solving linear interval and parametric equations, Linear Algebra Appl., 574 (2019), 1–21. http://dx.doi.org/10.1016/j.laa.2019.03.019 doi: 10.1016/j.laa.2019.03.019
    [15] M. Hladik, New operator and method for solving real preconditioned interval linear equations, SIAM J. Numer. Anal., 52 (2014), 194–206. http://dx.doi.org/10.1137/130914358 doi: 10.1137/130914358
    [16] A. Neumaier, Further results on linear interval equations, Linear Algebra Appl., 87 (1987), 155–179. http://dx.doi.org/10.1016/0024-3795(87)90164-9 doi: 10.1016/0024-3795(87)90164-9
    [17] J. Chakravarty, M. Saha, Generalized interval AOR method for solving interval linear equations, Math. Found. Comput., 8 (2025), 16–35. http://dx.doi.org/10.3934/mfc.2023035 doi: 10.3934/mfc.2023035
    [18] M. Saha, J. Chakravarty, Convergence of generalized SOR, Jacobi and Gauss–Seidel methods for linear systems, Int. J. Appl. Comput. Math., 6 (2020), 77. http://dx.doi.org/10.1007/s40819-020-00830-5 doi: 10.1007/s40819-020-00830-5
    [19] A. Neumaier, New techniques for the analysis of linear interval equations, Linear Algebra Appl., 58 (1984), 273–325. http://dx.doi.org/10.1016/0024-3795(84)90217-9 doi: 10.1016/0024-3795(84)90217-9
    [20] J. Kuang, On the two-parameter overrelaxation method for numerical solution of large linear systems, J. Shanghai Norm. Univ., 4 (1983), 1–11.
    [21] W P. Zeng, On the convergence of the TOR iterative method, Numer. Math. J. Chinese Univ., 8 (1986), 65–71.
    [22] M. M. Martins, D. J. Evans, M. E. Trigo, Convergence of the interval and point TOR method, Int. J. Comput. Math., 80 (2003), 1227–1241. http://dx.doi.org/10.1080/00207160310001624179 doi: 10.1080/00207160310001624179
    [23] S. M. Rump, INTLAB-INTerval LABoratory, In: Developments in reliable computing, Dordrecht: Springer, 1999, 77–104. https://doi.org/10.1007/978-94-017-1247-7_7
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