A modified CG-DESCENT method for unconstrained optimization

DOI10.1016/j.cam.2011.01.046zbMath1231.90343OpenAlexW2059598572MaRDI QIDQ535462

Feng-Hua Wen, Zhi-feng Dai

Publication date: 11 May 2011

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2011.01.046

zbMATH Keywords

CG-DESCENTconjugate gradient method, global convergenceunconstrainted optimization

Mathematics Subject Classification ID

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

Related Items (6)

A limited memory descent Perry conjugate gradient method ⋮ Optimal two-parameter geometric and arithmetic mean bounds for the Sándor-Yang mean ⋮ A note on generalized convex functions ⋮ Some new fractional integral inequalities for exponentially \(m\)-convex functions via extended generalized Mittag-Leffler function ⋮ Hermite-Hadamard type inequalities for co-ordinated convex and qausi-convex functions and their applications ⋮ A modified Perry conjugate gradient method and its global convergence

Uses Software

• CUTEr
• CUTE

Cites Work

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• Efficient generalized conjugate gradient algorithms. I: Theory
• Global convergence of the Fletcher-Reeves algorithm with inexact linesearch
• Global convergence of a modified Fletcher-Reeves conjugate gradient method with Armijo-type line search
• A descent modified Polak–Ribière–Polyak conjugate gradient method and its global convergence
• Descent Property and Global Convergence of the Fletcher—Reeves Method with Inexact Line Search
• 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
• Function minimization by conjugate gradients
• A Two-Term PRP-Based Descent Method
• Convergence Conditions for Ascent Methods
• The conjugate gradient method in extremal problems
• Methods of conjugate gradients for solving linear systems
• New conjugacy conditions and related nonlinear conjugate gradient methods
• Benchmarking optimization software with performance profiles.

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