Convergence analysis of preconditioned AOR iterative method for linear systems
Summary: \(M\)-(\(H\)-)matrices appear in many areas of science and engineering, for example, in the solution of the linear complementarity problem (LCP) in optimization theory and in the solution of large systems for real-time changes of data in fluid analysis in car industry. Classical (stationary) iterative methods used for the solution of linear systems have been shown to convergence for this class of matrices. In this paper, we present some comparison theorems on the preconditioned accelerated overrelaxation (AOR) iterative method for solving the linear system. Comparison results show that the rate of convergence of the preconditioned iterative method is faster than the rate of convergence of the classical iterative method. Meanwhile, we apply the preconditioner to \(H\)-matrices and obtain the convergence result. Numerical examples are given to illustrate our results.
accelerated overrelaxation (AOR) iterative method
scientific article; zbMATH DE number 5793738
scientific article