Convergence and dynamical study of a new sixth order convergence iterative scheme for solving nonlinear systems

Capdevila, Raudys R.; Cordero, Alicia; Torregrosa, Juan R.

doi:10.3934/math.2023642

Cited by 1 publication

(1 citation statement)

References 27 publications

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“…Recently, Al-Obaidi and Darvish [7] gave a comparative study on the qualification criteria for three categories nonlinear solvers for solving nonlinear equations. The multi-point and higher-order iterative algorithms based on the Newton technique for solving nonlinear equations can be seen in [8,9].…”

Section: Introductionmentioning

confidence: 99%

Optimal Combination of the Splitting–Linearizing Method to SSOR and SAOR for Solving the System of Nonlinear Equations

Liu,

El-Zahar,

Chang

2024

Mathematics

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The symmetric successive overrelaxation (SSOR) and symmetric accelerated overrelaxation (SAOR) are conventional iterative methods for solving linear equations. In this paper, novel approaches are presented by combining a splitting–linearizing method with SSOR and SAOR for solving a system of nonlinear equations. The nonlinear terms are decomposed at two sides through a splitting parameter, which are linearized around the values at the previous step, obtaining a linear equation system at each iteration step. The optimal values of parameters are determined to minimize the reciprocal of the maximal projection, which are sought in preferred ranges using the golden section search algorithm. Numerical tests assess the performance of the developed methods, namely, the optimal splitting symmetric successive over-relaxation (OSSSOR), and the optimal splitting symmetric accelerated over-relaxation (OSSAOR). The chief advantages of the proposed methods are that they do not need to compute the inverse matrix at each iteration step, and the computed orders of convergence by OSSSOR and OSSAOR are between 1.5 and 5.61; they, without needing the inner iterations loop, converge very fast with saving CPU time to find the true solution with a high accuracy.

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Section: Introductionmentioning

confidence: 99%