scholarly journals GLOBAL CONVERGENCE RESULTS OF A NEW THREE-TERM MEMORY GRADIENT METHOD

2004 ◽  
Vol 47 (2) ◽  
pp. 63-72
Author(s):  
Sun Qingying ◽  
Liu Xinhai
Keyword(s):  
Global Convergence ◽  
Gradient Method ◽  
Term Memory ◽  
Convergence Results ◽  
Memory Gradient Method

CONVERGENCE PROPERTY AND MODIFICATIONS OF A MEMORY GRADIENT METHOD

2005 ◽  
Vol 22 (04) ◽  
pp. 463-477 ◽  
Author(s):  
ZHEN-JUN SHI ◽  
JIE SHEN
Keyword(s):  
Global Convergence ◽  
Rate Of Convergence ◽  
Gradient Method ◽  
Large Scale ◽  
Convergence Property ◽  
Gradient Methods ◽  
Numerical Results ◽  
Minimization Problems ◽  
Memory Gradient Method

We study properties of a modified memory gradient method, including the global convergence and rate of convergence. Numerical results show that modified memory gradient methods are effective in solving large-scale minimization problems.

Strong global convergence of an adaptive nonmonotone memory gradient method

2007 ◽  
Vol 185 (1) ◽  
pp. 681-688 ◽  
Author(s):  
Zhensheng Yu ◽  
Weiguo Zhang ◽  
Baofeng Wu
Keyword(s):  
Global Convergence ◽  
Gradient Method ◽  
Memory Gradient Method

A modified Perry conjugate gradient method and its global convergence

2014 ◽  
Vol 9 (5) ◽  
pp. 999-1015 ◽  
Author(s):  
Ioannis E. Livieris ◽  
Panagiotis Pintelas
Keyword(s):  
Global Convergence ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method

scholarly journals A modified Perry-type derivative-free projection method for solving large-scale nonlinear monotone equations

2021 ◽  
Author(s):  
Mompati Koorapetse ◽  
P Kaelo ◽  
S Kooepile-Reikeletseng
Keyword(s):  
Global Convergence ◽  
Projection Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Large Scale ◽  
Numerical Results ◽  
Projection Technique ◽  
Monotone Equations ◽  
Derivative Free ◽  
Nonlinear Monotone Equations

In this paper, a new modified Perry-type derivative-free projection method for solving large-scale nonlinear monotone equations is presented. The method is developed by combining a modified Perry's conjugate gradient method with the hyperplane projection technique. Global convergence and numerical results of the proposed method are established. Preliminary numerical results show that the proposed method is promising and efficient compared to some existing methods in the literature.

scholarly journals Strict lower subdifferentiability and applications

1999 ◽  
Vol 40 (3) ◽  
pp. 379-391 ◽  
Author(s):  
H. Xu ◽  
A. M. Rubinov ◽  
B. M. Glover
Keyword(s):  
Global Convergence ◽  
Optimality Conditions ◽  
Convex Subset ◽  
Sufficient Optimality Conditions ◽  
Descent Direction ◽  
Minimization Problems ◽  
Convergence Results ◽  
Lower Subdifferential ◽  
Necessary And Sufficient ◽  
Convex Subdifferential

AbstractWe investigate the strict lower subdifferentiability of a real-valued function on a closed convex subset of Rn. Relations between the strict lower subdifferential, lower subdifferential, and the usual convex subdifferential are established. Furthermore, we present necessary and sufficient optimality conditions for a class of quasiconvex minimization problems in terms of lower and strict lower subdifferentials. Finally, a descent direction method is proposed and global convergence results of the consequent algorithm are obtained.

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