Abstract

In this paper, we introduce a class of non-monotone conjugate gradient methods, which include the well-known Polak-Ribiere method and Hestenes-Stiefel method as special cases. This class of nonmonotone conjugate gradient methods is proved to be globally convergent when it is applied to solve unconstrained optimization problems with convex objective functions

Information

Item Type:	Conference
Divisions:	» Laboratory of Computer Science and Mathematics » Faculty of Science and Technology
ePrint ID:	133
Date Deposited:	2014-11-22
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/133

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