Practical Mathematical Optimization

Practical Mathematical Optimization

Basic Optimization Theory and Gradient-Based Algorithms

Wilke, Daniel N; Snyman, Jan A

Springer International Publishing AG

05/2018

372

Dura

Inglês

9783319775852

15 a 20 dias

764

Descrição não disponível.
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.
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Mathematica;algorithms;linear optimization;optimization;programming;Python;multi-modal optimization;non-smooth optimization;discontinuous optimization;Numerical Linear Algebra;Hessian matrix approximations;Gradient-only solution strategies;Karush-Kuhn-Tucker theory;Quadratic programming;line search descent algorithm for unconstrained minimization;Unconstrained one-dimensional minimization