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Journal of Information and Optimization Sciences

(Since 1980)
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

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Journal of Information and Optimization Sciences
Open Access Research Article

Using a new hybrid conjugate gradient method with descent property

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pp. 1287–1302Vol. 44Issue 7October 2023DOI: 10.47974/JIOS-1176XML
Received:
04 Mar 2022
Published Online:
19 Oct 2023
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1176
Pages:
1287–1302

Abstract

The conjugate gradient method was an efficient technique for solving optimization problems. In this paper, we propose a new efficient (CG) coefficient bk,  is computed as a convex combination of Salleh and Alhawarat algorithm and CG-Descent algorithm. We prove the sufficient descent condition and the global convergence of the proposed method. It is established that the ak  satisfies the strong Wolfe line search conditions. The numerical results indicate that our method is robust and competitive.

Keywords

Unconstrained optimizationHybrid conjugate gradient methodStrong Wolfe conditions

Subject Classifications

49M3765K0590C06

References

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