New family of conjugate gradient methods with sufficient descent condition and global convergence for unconstrained optimizations
Conjugate gradient methods are a family of significance methods for solving of large-scale unconstrained optimization problems. This is due to both the simplicity of its algorithm and low memory requirement. A lot of efforts have been done to improve those methods since 1964 when the work of Flet...
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| Format: | Thesis Book |
| Language: | English |
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Table of Contents:
- 1. Introduction of research
- 2. The elementary concept of unconstrained optimizations
- 3. Conjugate gradient (CG) methods
- 4. New modifications of CG methods
- 5. Numerical results and discussion
- 6. Conclusion and suggestions