Practical Mathematical Optimization Basic Optimization Theory and Gradient-Based Algorithms /

• Κύριοι συγγραφείς: Snyman, Jan A. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Wilke, Daniel N. (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 2nd ed. 2018.
• Σειρά: Springer Optimization and Its Applications, 133
• Θέματα: Mathematical optimization.; Algorithms.; Operations research.; Management science.; Numerical analysis.; Computer software.; Functions of real variables.; Optimization.; Operations Research, Management Science.; Numerical Analysis.; Mathematical Software.; Real Functions.

This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are presented with emphasis on gradient-based numerical optimi...

Πίνακας περιεχομένων:

• 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.