The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization
We propose and generalize a new nonlinear conjugate gradient method for unconstrained optimization. The global convergence is proved with the Wolfe line search. Numerical experiments are reported which support the theoretical analyses and show the presented methods outperforming CGDESCENT method.
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
|
| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/932980 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832551691834097664 |
|---|---|
| author | Yang Yueting Cao Mingyuan |
| author_facet | Yang Yueting Cao Mingyuan |
| author_sort | Yang Yueting |
| collection | DOAJ |
| description | We propose and generalize a new nonlinear conjugate gradient method for unconstrained optimization. The global convergence is proved with the Wolfe line
search. Numerical experiments are reported which support the theoretical analyses and show the presented methods outperforming CGDESCENT method. |
| format | Article |
| id | doaj-art-9f77ae59c02249b895011fbb8fae3ce0 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-9f77ae59c02249b895011fbb8fae3ce02025-02-03T06:00:47ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/932980932980The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained OptimizationYang Yueting0Cao Mingyuan1School of Mathematics, Beihua University, Jilin 132013, ChinaSchool of Mathematics, Beihua University, Jilin 132013, ChinaWe propose and generalize a new nonlinear conjugate gradient method for unconstrained optimization. The global convergence is proved with the Wolfe line search. Numerical experiments are reported which support the theoretical analyses and show the presented methods outperforming CGDESCENT method.http://dx.doi.org/10.1155/2012/932980 |
| spellingShingle | Yang Yueting Cao Mingyuan The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization Journal of Applied Mathematics |
| title | The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization |
| title_full | The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization |
| title_fullStr | The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization |
| title_full_unstemmed | The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization |
| title_short | The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization |
| title_sort | global convergence of a new mixed conjugate gradient method for unconstrained optimization |
| url | http://dx.doi.org/10.1155/2012/932980 |
| work_keys_str_mv | AT yangyueting theglobalconvergenceofanewmixedconjugategradientmethodforunconstrainedoptimization AT caomingyuan theglobalconvergenceofanewmixedconjugategradientmethodforunconstrainedoptimization AT yangyueting globalconvergenceofanewmixedconjugategradientmethodforunconstrainedoptimization AT caomingyuan globalconvergenceofanewmixedconjugategradientmethodforunconstrainedoptimization |