Abstract
Recently, conjugate gradient methods, which usually generate descent search directions, are useful for large-scale optimization. Narushima et al. (SIAM J Optim 21:212–230, 2011) have proposed a three-term conjugate gradient method which satisfies a sufficient descent condition. We extend this method to two parameters family of three-term conjugate gradient methods which can be used to control the magnitude of the directional derivative. We show that these methods converge globally and work well for suitable choices of the parameters. Numerical results are also presented.
Original language | English |
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Pages (from-to) | 89-110 |
Number of pages | 22 |
Journal | Computational Optimization and Applications |
Volume | 60 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2014 |
Keywords
- Global convergence
- Sufficient descent condition
- Three-term conjugate gradient method
- Unconstrained optimization
ASJC Scopus subject areas
- Control and Optimization
- Computational Mathematics
- Applied Mathematics