A new type of conjugate gradient methods with sufficient descent property for unconstrained optimization

dc.contributor.author	Abashar, Abdelrhaman
dc.date.accessioned	2016-11-19T03:31:48Z
dc.date.available	2016-11-19T03:31:48Z
dc.date.issued	2014-08
dc.identifier.uri	http://hdl.handle.net/123456789/4719
dc.description.abstract	Conjugate gradient methods (CG) have an important part in unconstrained optimizations. Numerous studies and modifications have been concerned to improve these methods. In this study, two modifications of the CG coefficient (Bk) are proposed in a way to solve unconstrained optimization problems using exact line searches and inexact line searches by employing strong Wolfe line search.	en_US
dc.language.iso	en	en_US
dc.publisher	Terengganu: Universiti Malaysia Terengganu	en_US
dc.subject	QA 218 .A2 2014	en_US
dc.subject	Abashar, Abdelrhaman	en_US
dc.subject	Tesis PPIMG 2014	en_US
dc.subject	Conjugate gradient methods	en_US
dc.title	A new type of conjugate gradient methods with sufficient descent property for unconstrained optimization	en_US
dc.type	Thesis	en_US