Optimal scaling parameters for spectral conjugate gradient methods

DOI10.1007/s43069-022-00141-zzbMath1490.90304OpenAlexW4281808068MaRDI QIDQ2153393

Yanyan Li

Publication date: 4 July 2022

Published in: SN Operations Research Forum (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s43069-022-00141-z

zbMATH Keywords

unconstrained optimizationglobal convergencecondition numberspectral conjugate gradient method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Methods of quasi-Newton type (90C53) Numerical methods based on nonlinear programming (49M37)

Uses Software

• CUTEr
• CG_DESCENT
• Algorithm 500
• SCALCG

Cites Work

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• Convergence rates for Kaczmarz-type algorithms
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• Optimization theory and methods. Nonlinear programming
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• Spectral conjugate gradient methods with sufficient descent property for large-scale unconstrained optimization
• Algorithm 851
• Algorithm 500: Minimization of Unconstrained Multivariate Functions [E4]
• A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
• A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
• Function minimization by conjugate gradients
• CUTEr and SifDec
• The conjugate gradient method in extremal problems
• A spectral conjugate gradient method for unconstrained optimization
• Benchmarking optimization software with performance profiles.
• An efficient adaptive scaling parameter for the spectral conjugate gradient method

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