A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems
The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. This paper proposes a conjugate gradient method which is similar to Dai-Liao conjugate gradient method (Dai and Liao, 2001)...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/730454 |
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| _version_ | 1832559501120634880 |
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| author | Shengwei Yao Xiwen Lu Zengxin Wei |
| author_facet | Shengwei Yao Xiwen Lu Zengxin Wei |
| author_sort | Shengwei Yao |
| collection | DOAJ |
| description | The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear
optimization problems due to the simplicity of their very low memory requirements. This paper
proposes a conjugate gradient method which is similar to Dai-Liao conjugate gradient method (Dai and Liao, 2001)
but has stronger convergence properties. The given method possesses the sufficient descent condition,
and is globally convergent under strong Wolfe-Powell (SWP) line search for general function. Our
numerical results show that the proposed method is very efficient for the test problems. |
| format | Article |
| id | doaj-art-92df0c5acc9e4e7a8c0e971606b0536b |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-92df0c5acc9e4e7a8c0e971606b0536b2025-02-03T01:29:59ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/730454730454A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization ProblemsShengwei Yao0Xiwen Lu1Zengxin Wei2School of Science, East China University of Science and Technology, Shanghai 200237, ChinaSchool of Science, East China University of Science and Technology, Shanghai 200237, ChinaCollege of Mathematics and Information Science, Guangxi University, Nanning 530004, ChinaThe conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. This paper proposes a conjugate gradient method which is similar to Dai-Liao conjugate gradient method (Dai and Liao, 2001) but has stronger convergence properties. The given method possesses the sufficient descent condition, and is globally convergent under strong Wolfe-Powell (SWP) line search for general function. Our numerical results show that the proposed method is very efficient for the test problems.http://dx.doi.org/10.1155/2013/730454 |
| spellingShingle | Shengwei Yao Xiwen Lu Zengxin Wei A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems Journal of Applied Mathematics |
| title | A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems |
| title_full | A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems |
| title_fullStr | A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems |
| title_full_unstemmed | A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems |
| title_short | A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems |
| title_sort | conjugate gradient method with global convergence for large scale unconstrained optimization problems |
| url | http://dx.doi.org/10.1155/2013/730454 |
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