An Efficient Hybrid Conjugate Gradient Coefficient u nder Inexact Line Search

2020 ◽  
Vol 9 (1) ◽  
pp. 784-788
Author(s):  
Talat Alkhouli
Keyword(s):  
Conjugate Gradient ◽  
Line Search ◽  
Inexact Line Search

scholarly journals An n-th section line search in conjugate gradient method for small-scale unconstrained optimization

2017 ◽  
Vol 13 (4) ◽  
pp. 588-592
Author(s):  
Muhammad Imza Fakhri ◽  
Mohd Rivaie Mohd Ali ◽  
Ibrahim Jusoh
Keyword(s):  
Unconstrained Optimization ◽  
Conjugate Gradient ◽  
Line Search ◽  
Optimization Problem ◽  
Small Scale ◽  
Bisection Method ◽  
Inexact Line Search ◽  
Unconstrained Optimization Problem ◽  
Ideal Method ◽  
Bisection Line

Conjugate Gradient (CG) methods are well-known method for solving unconstrained optimization problem and popular for its low memory requirement. A lot of researches and efforts have been done in order to improve the efficiency of this CG method. In this paper, a new inexact line search is proposed based on Bisection line search. Initially, Bisection method is the easiest method to solve root of a function. Thus, it is an ideal method to employ in CG method. This new modification is named n-th section. In a nutshell, this proposed method is promising and more efficient compared to the original Bisection line search. 

scholarly journals Global convergence of conjugate gradient method in unconstrained optimization problems

2019 ◽  
Vol 38 (7) ◽  
pp. 227-231
Author(s):  
Huda Younus Najm ◽  
Eman T. Hamed ◽  
Huda I. Ahmed
Keyword(s):  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Line Search ◽  
Optimization Problems ◽  
Inexact Line Search ◽  
Sufficient Descent Condition ◽  
Unconstrained Optimization Problems ◽  
Sufficient Descent ◽  
Descent Condition

In this study, we propose a new parameter in the conjugate gradient method. It is shown that the new method fulfils the sufficient descent condition with the strong Wolfe condition when inexact line search has been used. The numerical results of this suggested method also shown that this method outperforms to other standard conjugate gradient method.

scholarly journals A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xiangrong Li ◽  
Songhua Wang ◽  
Zhongzhou Jin ◽  
Hongtruong Pham
Keyword(s):  
Conjugate Gradient ◽  
Large Scale ◽  
Line Search ◽  
Optimization Problems ◽  
Conjugate Gradient Algorithm ◽  
Gradient Algorithm ◽  
Search Technique ◽  
Inexact Line Search ◽  
Line Search Technique ◽  
Large Scale Unconstrained Optimization

This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following properties: (1) the new search direction possesses not only a sufficient descent property but also a trust region feature; (2) the presented algorithm has global convergence for nonconvex functions; (3) the numerical experiment showed that the new algorithm is more effective than similar algorithms.

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