New conjugate gradient-like methods for unconstrained optimization

DOI10.1080/10556788.2014.898764zbMath1308.65090OpenAlexW1979612361MaRDI QIDQ2926084

Bin Dan, Yang Zhang

Publication date: 29 October 2014

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

Full work available at URL: https://doi.org/10.1080/10556788.2014.898764

zbMATH Keywords

unconstrained optimizationglobal convergenceconjugate gradient methodline searchsufficient descent condition

Mathematics Subject Classification ID

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

Uses Software

• CG_DESCENT

Cites Work

• A new general form of conjugate gradient methods with guaranteed descent and strong global convergence properties
• A gradient-related algorithm with inexact line searches
• Global convergence of a memory gradient method for unconstrained optimization
• Global convergence result for conjugate gradient methods
• Global convergence of the Fletcher-Reeves algorithm with inexact linesearch
• Memory gradient method for the minimization of functions
• Study on a supermemory gradient method for the minimization of functions
• A Three-Term Conjugate Gradient Method with Sufficient Descent Property for Unconstrained Optimization
• Algorithm 851
• Descent Property and Global Convergence of the Fletcher—Reeves Method with Inexact Line Search
• Two-Point Step Size Gradient Methods
• Global Convergence Properties of Conjugate Gradient Methods for Optimization
• Convergence properties of the Fletcher-Reeves method
• A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
• Function minimization by conjugate gradients
• A Two-Term PRP-Based Descent Method
• CUTEr and SifDec
• New conjugacy conditions and related nonlinear conjugate gradient methods
• Benchmarking optimization software with performance profiles.

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