2022 Volume 12 Issue 4
Article Contents

Li-Tao Zhang, Ying-Chao Zhao, Yi-Fan Zhang, Sheng-Kun Li. RELAXED MODULUS-BASED SYNCHRONOUS MULTISPLITTING MULTI-PARAMETERS TOR (TWO-PARAMETERS OVER-RELAXATION) METHODS FOR LINEAR COMPLEMENTARITY PROBLEMS[J]. Journal of Applied Analysis & Computation, 2022, 12(4): 1403-1417. doi: 10.11948/20210166
Citation: Li-Tao Zhang, Ying-Chao Zhao, Yi-Fan Zhang, Sheng-Kun Li. RELAXED MODULUS-BASED SYNCHRONOUS MULTISPLITTING MULTI-PARAMETERS TOR (TWO-PARAMETERS OVER-RELAXATION) METHODS FOR LINEAR COMPLEMENTARITY PROBLEMS[J]. Journal of Applied Analysis & Computation, 2022, 12(4): 1403-1417. doi: 10.11948/20210166

RELAXED MODULUS-BASED SYNCHRONOUS MULTISPLITTING MULTI-PARAMETERS TOR (TWO-PARAMETERS OVER-RELAXATION) METHODS FOR LINEAR COMPLEMENTARITY PROBLEMS

  • In 2013, Bai and Zhang [Numerical Linear Algebra with Applications, 20(2013), 425–439] constructed modulus-based synchronous multisplitting methods by an equivalent reformulation of the linear complementarity problems into a system of fixed-point equations and studied the convergence of them. In 2014, Zhang and Li [Computers and Mathematics with Application, 67(2014), 1954–1959] analyzed and obtained the weaker convergence results for linear complementarity problems. In 2008, Zhang et.al. [International Journal of Computer Mathematics, 85(2), 2008, 211–224] presented global relaxed non-stationary multisplitting multi-parameter method by introducing some relaxed parameters. In this paper, we generalize Bai and Zhang's methods and study relaxed modulus-based synchronous multisplitting multi-parameters TOR (two-parameters over-relaxation, abbreviated as TOR) methods for linear complementarity problems. Furthermore, the convergence results of our new method in this paper are given when the system matrix is an $ H_{+}- $matrix.

    MSC: 65F10, 65F50, 90C33, 65G40
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