Abstract

In this paper, a new conjugate gradient method is pro-
posed for large-scale unconstrained optimization. This method includes
the already existing three practical nonlinear conjugate gradient meth-
ods, which produces a descent search direction at every iteration and
converges globally provided that the line search satis?es the Wolfe con-
ditions. The numerical experiments are done to test the e?ciency of
the new method, which con?rms the promising potentials of the new
method.

Information

Item Type:	Journal
Divisions:	» Laboratory of Computer Science and Mathematics » Faculty of Science and Technology
ePrint ID:	515
Date Deposited:	2016-04-01
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/515

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