Convergence of algorithms in optimization and solutions of nonlinear equations

DOI10.1007/s10957-009-9583-7zbMath1183.90386OpenAlexW1982425125MaRDI QIDQ848721

Bean San Goh

Publication date: 5 March 2010

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-009-9583-7

zbMATH Keywords

unconstrained optimizationconvergenceLyapunov functionrates of convergenceNewton methodsteepest descent methodsolutions of equations

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items (5)

Convergence and stability of line search methods for unconstrained optimization ⋮ On a two-phase approximate greatest descent method for nonlinear optimization with equality constraints ⋮ Newton methods to solve a system of nonlinear algebraic equations ⋮ Explicit pseudo-transient continuation and the trust-region updating strategy for unconstrained optimization ⋮ On the bang-bang control approach via a component-wise line search strategy for unconstrained optimization

Cites Work

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• A gradient-related algorithm with inexact line searches
• Algorithms for unconstrained optimization problems via control theory
• A. M. Lyapunov's stability theory—100 years on
• Continuous state feedback guaranteeing uniform ultimate boundedness for uncertain dynamic systems
• Global Convergence Properties of Conjugate Gradient Methods for Optimization
• Global convergence of some differential equation algorithms for solving equations involving positive variables
• Numerical Optimization
• Recent Advances in Liapunov Stability Theory
• Stability of Difference Equations and Convergence of Iterative Processes

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