On the convergence of curvilinear search algorithms in unconstrained optimization

DOI10.1016/0167-6377(85)90048-3zbMath0568.90081OpenAlexW1985169854MaRDI QIDQ1061006

Jorge Amaya

Publication date: 1985

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-6377(85)90048-3

zbMATH Keywords

unconstrained optimizationcurvilinear algorithmsgradient path approximation algorithmstrust region curvilinear algorithm

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Numerical methods based on nonlinear programming (49M37)

Cites Work

• A Newton-type curvilinear search method for optimization
• Minimization of functions having Lipschitz continuous first partial derivatives
• Quasi-Newton Methods, Motivation and Theory
• A new arc algorithm for unconstrained optimization
• Unconstrained Optimization by Approximation of the Gradient Path
• Curvilinear path and trust region in unconstrained optimization: A convergence analysis

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