New conjugate gradient method for unconstrained optimization
Sellami, Badreddine1 ; Chaib, Yacine1
1 Department of mathematics and informatics, Mohamed Cherif Messaadia University, Souk-Ahras, Algeria.
RAIRO - Operations Research - Recherche Opérationnelle, Special issue - Advanced Optimization Approaches and Modern OR-Applications, Tome 50 (2016) no. 4-5, pp. 1013-1026.

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.

DOI : 10.1051/ro/2015064
Classification : 65K05, 90C25, 90C26, 90C27, 90C30
Mots-clés : Unconstrained optimization, conjugate gradient method, line search, global convergence
Sellami, Badreddine 1 ; Chaib, Yacine 1

1 Department of mathematics and informatics, Mohamed Cherif Messaadia University, Souk-Ahras, Algeria. 
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Sellami, Badreddine; Chaib, Yacine. New conjugate gradient method for unconstrained optimization. RAIRO - Operations Research - Recherche Opérationnelle, Special issue - Advanced Optimization Approaches and Modern OR-Applications, Tome 50 (2016) no. 4-5, pp. 1013-1026. doi : 10.1051/ro/2015064. http://www.numdam.org/articles/10.1051/ro/2015064/

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