Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/18895
Title: Global Convergence of a New Coefficient Nonlinear Conjugate Gradient Method
Authors: Nur Syarafina Mohamed
Mustafa Mamat
Mohd Rivaie
Shazlyn Milleana Shaharuddin.
(UniKL MITEC)
Keywords: Conjugate Gradient Method
Strong Wolfe-Powell Line search
Global convergence
Issue Date: 8-May-2018
Series/Report no.: Vol. 5, No. 3, March 2017, pp. 401 ~ 408;
Abstract: Nonlinear conjugate gradient (CG) methods are widely used in optimization field due to its efficiency for solving a large scale unconstrained optimization problems. Many studies and modifications have been developed in order to improve the method. The method is known to possess sufficient descend condition and its global convergence properties under strong Wolfe-Powell search direction. In this paper, the new coefficient of CG method is presented. The global convergence and sufficient descend properties of the new coefficient are established by using strong Wolfe-Powell line search direction. Results show that the new coefficient is able to globally converge under certain assumptions and theories.
Description: Venue: Avillion Legacy Melaka
URI: http://ir.unikl.edu.my/jspui/handle/123456789/18895
Appears in Collections:Conference Paper



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