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Research articles

ScienceAsia (): 306-311 |doi: 10.2306/scienceasia1513-1874...306


Global convergence of two spectral conjugate gradient methods


Mahdi Ghanbari, Tahir Ahmad*, Norma Alias, Mohammadreza Askaripour

 
ABSTRACT:     Two new nonlinear spectral conjugate gradient methods for solving unconstrained optimization problems are proposed. One is based on the Hestenes and Stiefel (HS) method and the spectral conjugate gradient method. The other is based on a mixed spectral HS-CD conjugate gradient method, which combines the advantages of the spectral conjugate gradient method, the HS method, and the CD method. The directions generated by the methods are descent directions for the objective function. Under mild conditions, we prove that the spectral conjugate gradient methods with an Armijo-type line search are globally convergent. Numerical results show the proposed methods are promising.

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Ibnu Sina Institute for Fundamental Science Studies, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

* Corresponding author, E-mail: tahir@ibnusina.utm.my

Received 19 Dec 2012, Accepted 8 May 2013