Sufficient descent three term conjugate gradient method via symmetric rank-one update for large-scale optimization
In this paper, we propose a three-term conjugate gradient method via the symmetric rank-one update. The basic idea is to exploit the good properties of the SR1 update in providing quality Hessian approximations to construct a conjugate gradient line search direction without the storage of matrices a...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/53933/1/Sufficient%20descent%20three%20term%20conjugate%20gradient%20method%20.pdf http://psasir.upm.edu.my/id/eprint/53933/ http://www.tandfonline.com/doi/abs/10.1080/02331934.2014.994625?journalCode=gopt20 |
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| Summary: | In this paper, we propose a three-term conjugate gradient method via the symmetric rank-one update. The basic idea is to exploit the good properties of the SR1 update in providing quality Hessian approximations to construct a conjugate gradient line search direction without the storage of matrices and possess the sufficient descent property. Numerical experiments on a set of standard unconstrained optimization problems showed that the proposed method is superior to many well-known conjugate gradient methods in terms of efficiency and robustness. |
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