A computational process for choosing the relaxation parameter in nonlinear SOR

DOI10.1007/BF02252731zbMath0584.65038MaRDI QIDQ1069675

B. George

Publication date: 1986

Published in: Computing (Search for Journal in Brave)

zbMATH Keywords

convergenceNumerical examplesminimum of a strictly convex functionalnonlinear successive-overrelaxation

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

Related Items (8)

Nonlinear SOR and mesh redistribution ⋮ On nonlinear SOR-like methods. II: Convergence of the SOR-Newton method for mildly nonlinear equations ⋮ On the extrapolation method and the USA algorithm ⋮ On maximum residual nonlinear Kaczmarz-type algorithms for large nonlinear systems of equations ⋮ On pseudoinverse-free block maximum residual nonlinear Kaczmarz method for solving large-scale nonlinear system of equations ⋮ A random direction algorithm for an intersection problem ⋮ Nonlinear Kaczmarz algorithms and their convergence ⋮ A practical choice of parameters in improved SOR-Newton method with orderings

Cites Work

• Nonlinear successive over-relaxation
• Numerical solution of nonlinear elliptic partial differential equations by a generalized conjugate gradient method
• On approximating extremals of functionals. II: Theory and generalizations related to boundary value problems for nonlinear differential equations
• Iteration Methods for Nonlinear Problems
• Numerical Solution of the Minimal Surface Equation

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