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Global convergence analysis of a new hybrid conjugate gradient method for unconstrained optimization problems

Abdullahi, I. and Ahmad, R. (2017) Global convergence analysis of a new hybrid conjugate gradient method for unconstrained optimization problems. Malaysian Journal of Fundamental and Applied Sciences, 13 (2). ISSN 2289-5981

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Official URL: http://dx.doi.org/10.11113/mjfas.v13n2.540

Abstract

In this paper, we propose a new hybrid conjugate gradient method for unconstrained optimization problems. The proposed method comprises of beta (DY), beta (WHY), beta (RAMI) and beta (New). The beta (New) was constructed purposely for this proposed hybrid method.The method possesses sufficient descent property irrespective of the line search. Under Strong Wolfe-Powell line search, we proved that the method is globally convergent. Numerical experimentation shows the effectiveness and robustness of the proposed method when compare with some hybrid as well as some modified conjugate gradient methods.

Item Type:Article
Uncontrolled Keywords:hybrid conjugate gradient method, Strong Wolfe-Powell, comprises of beta (DY)
Subjects:Q Science > Q Science (General)
Divisions:Science
ID Code:80916
Deposited By: Narimah Nawil
Deposited On:24 Jul 2019 00:10
Last Modified:24 Jul 2019 00:10

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