Numerical Optimization with Computational Errors

This book studies the approximate solutions of optimization problems in the presence of computational errors. A number of results are presented on the convergence behavior of algorithms in a Hilbert space; these algorithms are examined taking into account computational errors. The author illustrates...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Zaslavski, Alexander J. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
Σειρά:Springer Optimization and Its Applications, 108
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 1. Introduction
  • 2. Subgradient Projection Algorithm
  • 3. The Mirror Descent Algorithm
  • 4. Gradient Algorithm with a Smooth Objective Function
  • 5. An Extension of the Gradient Algorithm
  • 6. Weiszfeld's Method
  • 7. The Extragradient Method for Convex Optimization
  • 8. A Projected Subgradient Method for Nonsmooth Problems
  • 9. Proximal Point Method in Hilbert Spaces
  • 10. Proximal Point Methods in Metric Spaces
  • 11. Maximal Monotone Operators and the Proximal Point Algorithm
  • 12. The Extragradient Method for Solving Variational Inequalities
  • 13. A Common Solution of a Family of Variational Inequalities
  • 14. Continuous Subgradient Method
  • 15. Penalty Methods
  • 16. Newton's method
  • References
  • Index. .