Convergence of the descent Dai–Yuan conjugate gradient method for unconstrained optimization
From MaRDI portal
Publication:5208033
DOI10.1177/1077546311405750zbMath1429.65128OpenAlexW2069731254MaRDI QIDQ5208033
Masoud Hajarian, Mehdi Dehghan
Publication date: 15 January 2020
Published in: Journal of Vibration and Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1177/1077546311405750
unconstrained optimizationglobal convergenceconjugate gradient methodline searchdescent conditionGoldstein conditions
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A class of globally convergent conjugate gradient methods
- Convergence of Liu-Storey conjugate gradient method
- Efficient generalized conjugate gradient algorithms. I: Theory
- Optimization. Algorithms and consistent approximations
- Global convergence properties of nonlinear conjugate gradient methods with modified secant condition
- A Dai-Yuan conjugate gradient algorithm with sufficient descent and conjugacy conditions for unconstrained optimization
- Minimization of functions having Lipschitz continuous first partial derivatives
- Spectral conjugate gradient methods with sufficient descent property for large-scale unconstrained optimization
- Descent Property and Global Convergence of the Fletcher—Reeves Method with Inexact Line Search
- Numerical Optimization
- A family of hybrid conjugate gradient methods for unconstrained optimization
- 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
- The conjugate gradient method in extremal problems
- Methods of conjugate gradients for solving linear systems