Volume 50, Number 4-5, October-December 2016
|Page(s)||1013 - 1026|
|Published online||03 November 2016|
New conjugate gradient method for unconstrained optimization
Accepted: 21 December 2015
In this paper, a new conjugate gradient method is proposed for large-scale unconstrained optimization. This method includes the already existing three practical nonlinear conjugate gradient methods, which produces a descent search direction at every iteration and converges globally provided that the line search satisfies the Wolfe conditions. The numerical experiments are done to test the efficiency of the new method, which confirms the promising potentials of the new method.
Mathematics Subject Classification: 65K05 / 90C25 / 90C26 / 90C27 / 90C30
Key words: Unconstrained optimization / conjugate gradient method / line search / global convergence
© EDP Sciences, ROADEF, SMAI 2016
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