A modifications of conjugate gradient method for unconstrained optimization problems
The Conjugate Gradient (CG) methods play an important role in solving large-scale unconstrained optimization problems. Several studies have been recently devoted to improving and modifying these methods in relation to efficiency and robustness. In this paper, a new parameter of CG method has been pr...
| 出版年: | International Journal of Engineering and Technology(UAE) |
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| 第一著者: | |
| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Science Publishing Corporation Inc
2018
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| オンライン･アクセス: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045397706&doi=10.14419%2fijet.v7i2.14.11146&partnerID=40&md5=2149691b992d92af107809818ee076bd |
| 要約: | The Conjugate Gradient (CG) methods play an important role in solving large-scale unconstrained optimization problems. Several studies have been recently devoted to improving and modifying these methods in relation to efficiency and robustness. In this paper, a new parameter of CG method has been proposed. The new parameter possesses global convergence properties under the Strong Wolfe-Powell (SWP) line search. The numerical results show that the proposed formula is more efficient and robust compared with Polak-Rribiere Ployak (PRP), Fletcher-Reeves (FR) and Wei, Yao, and Liu (WYL) parameters. © 2018 Authors. |
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| ISSN: | 2227524X |
| DOI: | 10.14419/ijet.v7i2.14.11146 |