Conjugate gradient methods with sufficient descent condition for large-scale unconstrained optimization

In this paper, we make a modification to the standard conjugate gradient method so that its search direction satisfies the sufficient descent condition. We prove that the modified conjugate gradient method is globally convergent under Armijo line search. Numerical results show that the proposed conj...

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Bibliographic Details
Main Authors: Ling, Mei Mei, Leong, Wah June
Format: Conference Proceeding
Language:English
Subjects:
Conjugate gradient method
Conjugates
Descent
Distributed processing
Optimization
Queuing theory
Online Access:Get full text
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Summary:In this paper, we make a modification to the standard conjugate gradient method so that its search direction satisfies the sufficient descent condition. We prove that the modified conjugate gradient method is globally convergent under Armijo line search. Numerical results show that the proposed conjugate gradient method is efficient compared to some of its standard counterparts for large-scale unconstrained optimization.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4903647