A New Dai-Liao Conjugate Gradient Method with Optimal Parameter Choice

DOI10.1080/01630563.2018.1535506zbMath1411.90329OpenAlexW2900576582MaRDI QIDQ4632353

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Publication date: 29 April 2019

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630563.2018.1535506

zbMATH Keywords

unconstrained optimizationglobal convergenceconjugate gradient methodspectral condition numbersufficient descent condition

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items (6)

New nonlinear conjugate gradient methods based on optimal Dai-Liao parameters ⋮ An accelerated descent CG algorithm with clustering the eigenvalues for large-scale nonconvex unconstrained optimization and its application in image restoration problems ⋮ A three-term conjugate gradient method with a random parameter for large-scale unconstrained optimization and its application in regression model ⋮ On a scaled symmetric Dai-Liao-type scheme for constrained system of nonlinear equations with applications ⋮ A class of new three-term descent conjugate gradient algorithms for large-scale unconstrained optimization and applications to image restoration problems ⋮ Two descent Dai-Yuan conjugate gradient methods for systems of monotone nonlinear equations

Uses Software

• CUTEr
• SifDec

Cites Work

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