A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization
The nonlinear conjugate gradient algorithms are a very effective way in solving large-scale unconstrained optimization problems. Based on some famous previous conjugate gradient methods, a modified hybrid conjugate gradient method was proposed. The proposed method can generate decent directions at e...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/5597863 |
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| _version_ | 1832547022857568256 |
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| author | Minglei Fang Min Wang Min Sun Rong Chen |
| author_facet | Minglei Fang Min Wang Min Sun Rong Chen |
| author_sort | Minglei Fang |
| collection | DOAJ |
| description | The nonlinear conjugate gradient algorithms are a very effective way in solving large-scale unconstrained optimization problems. Based on some famous previous conjugate gradient methods, a modified hybrid conjugate gradient method was proposed. The proposed method can generate decent directions at every iteration independent of any line search. Under the Wolfe line search, the proposed method possesses global convergence. Numerical results show that the modified method is efficient and robust. |
| format | Article |
| id | doaj-art-8afe1ba54e164a6e80e1bc5cc173c582 |
| institution | Kabale University |
| issn | 2314-4629 2314-4785 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-8afe1ba54e164a6e80e1bc5cc173c5822025-02-03T06:46:22ZengWileyJournal of Mathematics2314-46292314-47852021-01-01202110.1155/2021/55978635597863A Modified Hybrid Conjugate Gradient Method for Unconstrained OptimizationMinglei Fang0Min Wang1Min Sun2Rong Chen3School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, ChinaSchool of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, ChinaSchool of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, ChinaSchool of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, ChinaThe nonlinear conjugate gradient algorithms are a very effective way in solving large-scale unconstrained optimization problems. Based on some famous previous conjugate gradient methods, a modified hybrid conjugate gradient method was proposed. The proposed method can generate decent directions at every iteration independent of any line search. Under the Wolfe line search, the proposed method possesses global convergence. Numerical results show that the modified method is efficient and robust.http://dx.doi.org/10.1155/2021/5597863 |
| spellingShingle | Minglei Fang Min Wang Min Sun Rong Chen A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization Journal of Mathematics |
| title | A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization |
| title_full | A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization |
| title_fullStr | A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization |
| title_full_unstemmed | A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization |
| title_short | A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization |
| title_sort | modified hybrid conjugate gradient method for unconstrained optimization |
| url | http://dx.doi.org/10.1155/2021/5597863 |
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