Multi-step spectral gradient methods with modified weak secant relation for large scale unconstrained optimization

DOI10.3934/NACO.2018024OpenAlexW2810759577WikidataQ129545232 ScholiaQ129545232MaRDI QIDQ1713247

Wah June Leong, Siti Nur Iqmal Ibrahim, Hong Seng Sim, Chuei Yee Chen

Publication date: 24 January 2019

Published in: Numerical Algebra, Control and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/naco.2018024

zbMATH Keywords

unconstrained optimizationlarge scalelog-determinant normmodified weak secant relationspectral gradient methods

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Numerical optimization and variational techniques (65K10)

Related Items (2)

Nonmonotone spectral gradient method based on memoryless symmetric rank-one update for large-scale unconstrained optimization ⋮ A survey of gradient methods for solving nonlinear optimization

Uses Software

• L-BFGS
• CUTEr
• CUTE

Cites Work

• Unnamed Item
• On the limited memory BFGS method for large scale optimization
• Multi-step quasi-Newton methods for optimization
• The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
• Sizing and Least-Change Secant Methods
• Two-Point Step Size Gradient Methods
• A Tool for the Analysis of Quasi-Newton Methods with Application to Unconstrained Minimization
• CUTE
• Nonmonotone Spectral Methods for Large-Scale Nonlinear Systems
• The Quasi-Cauchy Relation and Diagonal Updating
• Spectral residual method without gradient information for solving large-scale nonlinear systems of equations

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