Practical Mathematical Optimization: Basic Optimization Theory and Gradient-Based Algorithms (Hardcover, 2, 2018)

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.