Global convergence analysis of a new nonlinear conjugate gradient coefficient with strong Wolfe line search

2015 ◽  
Author(s):  
Awad Abdelrahman ◽  
Mustafa Mamat ◽  
Mohd Rivaie ◽  
Osman Omer
Keyword(s):  
Global Convergence ◽  
Convergence Analysis ◽  
Conjugate Gradient ◽  
Line Search ◽  
Nonlinear Conjugate Gradient ◽  
Global Convergence Analysis ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search

Global convergence of a new spectral conjugate gradient by using Strong Wolfe line search

2015 ◽  
Vol 9 ◽  
pp. 3105-3117 ◽  
Author(s):  
Norhaslinda Zull ◽  
Mohd Rivaie ◽  
Mustafa Mamat ◽  
Zabidin Salleh ◽  
Zahrahtul Amani
Keyword(s):  
Global Convergence ◽  
Conjugate Gradient ◽  
Line Search ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Spectral Conjugate Gradient

scholarly journals The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization

2012 ◽  
Vol 2012 ◽  
pp. 1-14
Author(s):  
Yang Yueting ◽  
Cao Mingyuan
Keyword(s):  
Global Convergence ◽  
Unconstrained Optimization ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Nonlinear Conjugate Gradient Method ◽  
Nonlinear Conjugate Gradient ◽  
Wolfe Line Search ◽  
Theoretical Analyses

We propose and generalize a new nonlinear conjugate gradient method for unconstrained optimization. The global convergence is proved with the Wolfe line search. Numerical experiments are reported which support the theoretical analyses and show the presented methods outperforming CGDESCENT method.

scholarly journals Global Convergence of a Nonlinear Conjugate Gradient Method

2011 ◽  
Vol 2011 ◽  
pp. 1-22
Author(s):  
Liu Jin-kui ◽  
Zou Li-min ◽  
Song Xiao-qian
Keyword(s):  
Global Convergence ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Optimization Problems ◽  
Nonlinear Conjugate Gradient Method ◽  
Unconstrained Optimization Problems ◽  
Nonlinear Conjugate Gradient ◽  
Wolfe Line Search

A modified PRP nonlinear conjugate gradient method to solve unconstrained optimization problems is proposed. The important property of the proposed method is that the sufficient descent property is guaranteed independent of any line search. By the use of the Wolfe line search, the global convergence of the proposed method is established for nonconvex minimization. Numerical results show that the proposed method is effective and promising by comparing with the VPRP, CG-DESCENT, and DL+methods.

Two-Parameter Conjugate Gradient Projection Method and its Application

2014 ◽  
Vol 989-994 ◽  
pp. 1802-1805
Author(s):  
Hong Fang Cui
Keyword(s):  
Conjugate Gradient Method ◽  
Projection Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Linear Constraints ◽  
Convergence Criteria ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Two Parameter

On the basis of the conjugate gradient method CD, the artile builds a new two-parameter P-NCD projected conjugate gradient method, the article gives two-parameter P-NCD Conjugate Gradient Method drop projection and on the strong Wolfe line search in the principles of the convergence criteria, the new algorithm is applied to estimate the equation with linear constraints in the model instantiated test ,the results shows good results.

scholarly journals A modified quadratic hybridization of Polak-Ribiere-Polyak and Fletcher-Reeves conjugate gradient method for unconstrained optimization problems

2017 ◽  
Vol 7 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Pro Kaelo ◽  
Sindhu Narayanan ◽  
M.V. Thuto
Keyword(s):  
Unconstrained Optimization ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Optimization Problems ◽  
Unconstrained Optimization Problems ◽  
Strong Wolfe Line Search ◽  
Wolfe Line Search ◽  
Hybrid Conjugate Gradient Method

This article presents a modified quadratic hybridization of the Polak–Ribiere–Polyak and Fletcher–Reeves conjugate gradient method for solving unconstrained optimization problems. Global convergence, with the strong Wolfe line search conditions, of the proposed quadratic hybrid conjugate gradient method is established. We also report some numerical results to show the competitiveness of the new hybrid method.

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