A new general form of conjugate gradient methods with guaranteed descent and strong global convergence properties

DOI10.1007/s11075-011-9515-0zbMath1245.65069OpenAlexW1979559025MaRDI QIDQ415335

Kairong Wang, Yang Zhang

Publication date: 8 May 2012

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11075-011-9515-0

zbMATH Keywords

global convergencenumerical resultsconjugate gradient methodline searchsufficient descent conditionconjugate-descent-typeDai-Yuan-typeHestenes-StiefelLiu-StoreyPolak-Ribière-Polyak

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

Related Items (1)

New conjugate gradient-like methods for unconstrained optimization

Uses Software

• L-BFGS
• CUTEr
• CG_DESCENT
• CUTE

Cites Work

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• A class of globally convergent conjugate gradient methods
• On the convergence property of the DFP algorithm
• On the limited memory BFGS method for large scale optimization
• Convergence Properties of Algorithms for Nonlinear Optimization
• Algorithm 851
• Global Convergence Properties of Conjugate Gradient Methods for Optimization
• CUTE
• A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
• A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
• Convergence Conditions for Ascent Methods
• Convergence Conditions for Ascent Methods. II: Some Corrections
• Methods of conjugate gradients for solving linear systems
• New properties of a nonlinear conjugate gradient method
• Benchmarking optimization software with performance profiles.

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