DocumentCode
175723
Title
Two modified PRP conjugate gradient methods with sufficient descent property for unconstrained optimization
Author
Yubin Zhou ; Zhongbo Sun ; Xudong Shi ; Yinghui Teng
Author_Institution
Coll. of Humanities & Sci., Northeast Normal Univ., Changchun, China
fYear
2014
fDate
May 31 2014-June 2 2014
Firstpage
1005
Lastpage
1009
Abstract
In this paper, we propose two modified conjugate gradient methods, which produce sufficient descent direction at every iteration. The theoretical analysis shows that the algorithms are global convergence under some suitable conditions. The numerical results show that both algorithms are efficient for the given test problems from the Matlab library.
Keywords
conjugate gradient methods; convergence; iterative methods; optimisation; Matlab library; descent property; global convergence; iteration; modified PRP conjugate gradient methods; unconstrained optimization; Algorithm design and analysis; Convergence; Educational institutions; Equations; Gradient methods; MATLAB; Conjugate gradient method; Global convergence; Sufficient descent direction; Unconstrained optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location
Changsha
Print_ISBN
978-1-4799-3707-3
Type
conf
DOI
10.1109/CCDC.2014.6852311
Filename
6852311
Link To Document