A new search direction of DFP-CG method for solving unconstrained optimization problems
The conjugate gradient (CG) and Davidon, Fletcher and Powell (DFP) method are both well known solvers for solving unconstrained optimization problems. In this paper, we proposed a new hybrid DFP-CG method and compared with the ordinary DFP method in terms of number of iteration and CPU times. Num...
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| 主要な著者: | , , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English English |
| 出版事項: |
2018
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| 主題: | |
| オンライン･アクセス: | http://eprints.unisza.edu.my/1664/1/FH03-FIK-18-14473.jpg http://eprints.unisza.edu.my/1664/2/FH03-FIK-18-16990.pdf http://eprints.unisza.edu.my/1664/ |
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| 要約: | The conjugate gradient (CG) and Davidon, Fletcher and Powell (DFP) method are both well known
solvers for solving unconstrained optimization problems. In this paper, we proposed a new hybrid
DFP-CG method and compared with the ordinary DFP method in terms of number of iteration and
CPU times. Numerical results show that the new algorithm is more efficient compared to the ordinary
DFP method and proven to posses both sufficient descent and global convergence properties. |
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