Two new conjugate gradient methods for unconstrained optimization

DOI10.1155/2020/9720653zbMath1435.90146OpenAlexW3018389197MaRDI QIDQ2179153

Jianghua Yin, Guodong Ma, Meixing Liu

Publication date: 12 May 2020

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2020/9720653

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of reduced gradient type (90C52)

Uses Software

• CUTEr
• minpack
• CUTE
• ACGSSV

Cites Work

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• Multi-objective global optimal parafoil homing trajectory optimization via Gauss pseudospectral method
• Efficient generalized conjugate gradient algorithms. I: Theory
• An improved Wei-Yao-Liu nonlinear conjugate gradient method for optimization computation
• Improved Fletcher-Reeves and Dai-Yuan conjugate gradient methods with the strong Wolfe line search
• Two modified nonlinear conjugate gradient methods with disturbance factors for unconstrained optimization
• Accelerated adaptive Perry conjugate gradient algorithms based on the self-scaling memoryless BFGS update
• A new version of the Liu-Storey conjugate gradient method
• Two optimal Dai–Liao conjugate gradient methods
• Testing Unconstrained Optimization Software
• CUTE
• A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
• Function minimization by conjugate gradients
• The conjugate gradient method in extremal problems
• Methods of conjugate gradients for solving linear systems
• Benchmarking optimization software with performance profiles.
• An efficient hybrid conjugate gradient method for unconstrained optimization

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