A hybridization of the Polak-Ribière-Polyak and Fletcher-Reeves conjugate gradient methods

DOI10.1007/s11075-014-9856-6zbMath1311.65066OpenAlexW2003894104WikidataQ57952646 ScholiaQ57952646MaRDI QIDQ2017614

Reza Ghanbari, Saman Babaie-Kafaki

Publication date: 23 March 2015

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

Full work available at URL: https://doi.org/10.1007/s11075-014-9856-6

zbMATH Keywords

unconstrained optimizationnumerical exampleglobal convergencelarge-scale optimizationconjugate gradient methodPolak-Ribière-Polyak method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30)

Related Items (8)

A descent hybrid conjugate gradient method based on the memoryless BFGS update ⋮ Quasi-Newton minimization for the \(p(x)\)-Laplacian problem ⋮ An efficient hybrid conjugate gradient method with sufficient descent property for unconstrained optimization ⋮ Existence, multiplicity and numerical examples for Schrödinger systems with nonstandard \(p(x)\)-growth conditions ⋮ Unnamed Item ⋮ Least-squares-based three-term conjugate gradient methods ⋮ A nonmonotone scaled Fletcher-Reeves conjugate gradient method with application in image reconstruction ⋮ A NEW THREE–TERM CONJUGATE GRADIENT METHOD WITH DESCENT DIRECTION FOR UNCONSTRAINED OPTIMIZATION

Uses Software

• CUTEr

Cites Work

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• Function minimization by conjugate gradients
• CUTEr and SifDec
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• The conjugate gradient method in extremal problems
• Benchmarking optimization software with performance profiles.

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