An efficient conjugate direction method with orthogonalization for large-scale quadratic optimization problems

DOI10.1080/10556780500532209zbMath1131.90460OpenAlexW2092852432MaRDI QIDQ5758225

Edouard R. Boudinov, Arkadiy I. Manevich

Publication date: 3 September 2007

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556780500532209

zbMATH Keywords

large-scale optimizationorthogonalizationunconstrained minimizationconjugate gradientsconjugate direction methods

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Quadratic programming (90C20) Methods of reduced gradient type (90C52)

Uses Software

• mctoolbox

Cites Work

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• Global Convergence Properties of Conjugate Gradient Methods for Optimization
• Restart procedures for the conjugate gradient method
• Algorithm 778: L-BFGS-B
• A Limited Memory Algorithm for Bound Constrained Optimization
• Function minimization by conjugate gradients
• The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
• The conjugate gradient method in extremal problems
• Conjugate Directions without Linear Searches

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