A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equations
Abstract For large-scale unconstrained optimization problems and nonlinear equations, we propose a new three-term conjugate gradient algorithm under the Yuan–Wei–Lu line search technique. It combines the steepest descent method with the famous conjugate gradient algorithm, which utilizes both the re...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-05-01
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| Series: | Journal of Inequalities and Applications |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13660-018-1703-1 |
| _version_ | 1818435986386845696 |
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| author | Gonglin Yuan Wujie Hu |
| author_facet | Gonglin Yuan Wujie Hu |
| author_sort | Gonglin Yuan |
| collection | DOAJ |
| description | Abstract For large-scale unconstrained optimization problems and nonlinear equations, we propose a new three-term conjugate gradient algorithm under the Yuan–Wei–Lu line search technique. It combines the steepest descent method with the famous conjugate gradient algorithm, which utilizes both the relevant function trait and the current point feature. It possesses the following properties: (i) the search direction has a sufficient descent feature and a trust region trait, and (ii) the proposed algorithm globally converges. Numerical results prove that the proposed algorithm is perfect compared with other similar optimization algorithms. |
| first_indexed | 2024-12-14T17:01:36Z |
| format | Article |
| id | doaj.art-440d380669c447f5b388f439730371df |
| institution | Directory Open Access Journal |
| issn | 1029-242X |
| language | English |
| last_indexed | 2024-12-14T17:01:36Z |
| publishDate | 2018-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Inequalities and Applications |
| spelling | doaj.art-440d380669c447f5b388f439730371df2022-12-21T22:53:49ZengSpringerOpenJournal of Inequalities and Applications1029-242X2018-05-012018111910.1186/s13660-018-1703-1A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equationsGonglin Yuan0Wujie Hu1College of Mathematics and Information Science, Guangxi UniversityCollege of Mathematics and Information Science, Guangxi UniversityAbstract For large-scale unconstrained optimization problems and nonlinear equations, we propose a new three-term conjugate gradient algorithm under the Yuan–Wei–Lu line search technique. It combines the steepest descent method with the famous conjugate gradient algorithm, which utilizes both the relevant function trait and the current point feature. It possesses the following properties: (i) the search direction has a sufficient descent feature and a trust region trait, and (ii) the proposed algorithm globally converges. Numerical results prove that the proposed algorithm is perfect compared with other similar optimization algorithms.http://link.springer.com/article/10.1186/s13660-018-1703-1Conjugate gradientDescent propertyGlobal convergence |
| spellingShingle | Gonglin Yuan Wujie Hu A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equations Journal of Inequalities and Applications Conjugate gradient Descent property Global convergence |
| title | A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equations |
| title_full | A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equations |
| title_fullStr | A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equations |
| title_full_unstemmed | A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equations |
| title_short | A conjugate gradient algorithm for large-scale unconstrained optimization problems and nonlinear equations |
| title_sort | conjugate gradient algorithm for large scale unconstrained optimization problems and nonlinear equations |
| topic | Conjugate gradient Descent property Global convergence |
| url | http://link.springer.com/article/10.1186/s13660-018-1703-1 |
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