On Conjugate Gradient Algorithms as Objects of Scientific Study

DOI10.1080/10556780310001603653zbMath1141.90544OpenAlexW2054409288MaRDI QIDQ4653551

John Lawrence Nazareth

Publication date: 7 March 2005

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

Full work available at URL: https://doi.org/10.1080/10556780310001603653

zbMATH Keywords

nonlinear optimizationconjugate gradientsmultialgorithmsalgorithmic sciencepopulation-thinking

Mathematics Subject Classification ID

Nonlinear programming (90C30) Methods of reduced gradient type (90C52)

Related Items (1)

On CG algorithms as objects of scientific study: An appendix

Uses Software

• MPI

Cites Work

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• Computational methods in optimization. A unified approach.
• Differentiable optimization and equation solving. A treatise on algorithmic science and the Karmarkar revolution
• Descent Property and Global Convergence of the Fletcher—Reeves Method with Inexact Line Search
• Restart procedures for the conjugate gradient method
• Convergence properties of the Fletcher-Reeves method
• A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
• Function minimization by conjugate gradients
• Convergence Conditions for Ascent Methods
• A new approach to variable metric algorithms
• The conjugate gradient method in extremal problems
• An efficient hybrid conjugate gradient method for unconstrained optimization

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