New Hybrid Conjugate Gradient Method Under Exact Line Search

DOI

10.2991/978-94-6463-014-5_10How to use a DOI?

Keywords

Hybrid conjugate gradient; Exact line search; Unconstrained optimization

Abstract

Conjugate gradient (CG) method is one of the popular method in solving unconstrained optimization problem. This method is notable for being an intermediate between the steepest descent method and the Newton’s method. In this study, a new hybrid CG method is proposed with the main focus on improving Aini-Rivaie-Mustafa (ARM) CG method that were introduced in 2016. The ARM CG method sometimes generates negative CG coefficient that affects the performance of the method. Therefore, the new hybrid CG method is proposed with the intention of eliminating the negative CG coefficient value generated by the ARM CG method. The new hybrid CG method is globally convergent under the exact minimization rules and based on the numerical observation, it shows that it could solve higher number of test problems, as compared to the ARM CG method.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ain Aqiela Azamuddin
AU  - Nurul ‘Aini
AU  - Mohd Rivaie
AU  - Zuraida Alwadood
PY  - 2022
DA  - 2022/12/12
TI  - New Hybrid Conjugate Gradient Method Under Exact Line Search
BT  - Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)
PB  - Atlantis Press
SP  - 94
EP  - 102
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-014-5_10
DO  - 10.2991/978-94-6463-014-5_10
ID  - Azamuddin2022
ER  -