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NONLINEAR CONJUGATE GRADIENT METHODS FOR
UNCONSTRAINED OPTIMIZATION
- Neculai Andrei
Nonlinear
Conjugate Gradient Methods for Unconstrained Optimization
Springer Optimization and Its Applications, Volume 158
Springer Science+Business Media New York 2020
ISBN: 978-3-030-42940-2
e-book ISBN: 978-3-030-42950-8
ISSN: 1931-6828
DOI: 10.1007/978-3-030-42950-8
Springer New York Heidelberg Dordrecht London
498 + XXIIIV pages.
NECULAI ANDREI
NONLINEAR CONJUGATE GRADIENT METHODS FOR
UNCONSTRAINED OPTIMIZATION
Preface
- Contents
- List of Figures
- List of Tables
- List of Algorithms
- 1. Introduction: Overview of Unconstrained Optimization
- 2. Linear Conjugate Gradient Algorithm
- 3. General Convergence Results for Nonlinear Conjugate Gradient Methods
- 4. Standard Conjugate Gradient Methods
- 5. Acceleration of Conjugate Gradient Algorithms
- 6. Hybrid and Parameterized Conjugate Gradient Methods
- 7. Conjugate Gradient Methods as Modifications of the Standard Schemes
- 8. Conjugate Gradient Methods Memoryless BFGS Preconditioned
- 9. Three-term Conjugate Gradient Methods
- 10. Preconditioning of the Nonlinear Conjugate Gradient Algorithms
- 11. Other Conjugate Gradient Methods
- 12. Discussions, Conclusions, and Large-Scale OPtimization
- Appendix A: Mathematical Review
- Appendix B: UOP: A Collection of 80 Unconstrained Optimization Test Problems
- References
- Author Index
- Subject Index