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

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...

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Bibliographische Detailangaben
1. Verfasser: Snyman, Jan A. (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Cham : Springer International Publishing, 2018.
Ausgabe:2nd ed. 2018.
Schriftenreihe:Springer Optimization and Its Applications, 133
Schlagworte:
Mathematical optimization.
Algorithms.
Operations research.
Management science.
Numerical analysis.
Computer software.
Functions of real variables.
ISBN:9783319775869
ISSN:1931-6828 ;
Online-Zugang: Volltext
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Inhaltsangabe:
  • 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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