Authors | |
Publisher | Springer, Berlin |
Year | |
Pages | 372 |
Version | hardback |
Language | English |
ISBN | 9783319775852 |
Categories | Optimization |
This book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form. It enables professionals to apply optimization theory to engineering, physics, chemistry, or business economics.
Practical Mathematical Optimization: Basic Optimization Theory and Gradient-Based Algorithms
1.Introduction.- 2.Line search descent methods for unconstrained minimization.-3. Standard methods for constrained optimization.-4. Basic Example Problems.- 5. Some Basic Optimization Theorems.- 6. New gradient-based trajectory and approximation methods.- 7. Surrogate Models.- 8. Gradient-only solution strategies.- 9. Practical computational optimization using Python.- Appendix.- Index.