Stochastic optimization methods

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Annotation Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insenistive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probabi...

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Bibliographic Details
Main Author: Marti, Kurt, 1943-
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berlin ; London : Springer, ©2008.
Berlin ; London : [2008]
Edition:2nd ed.
Physical Description:
1 online resource (xiii, 340 pages) : illustrations.
Subjects:
Stochastic processes.
Mathematical optimization.
economie.
economics.
bedrijfswetenschap.
management science.
engineering.
operationeel onderzoek.
operations research.
optimalisatie.
optimization.
numerieke methoden.
numerical methods.
computational science.
Management studies, Business Administration, Organizational Science (General)
Economics (General)
Management, bedrijfskunde, organisatiekunde (algemeen)
Economie (algemeen)
Online Access:SpringerLink - Click here for access
Contents:
  • pt. I. Basic Stochastic Optimization Methods
  • 1. Decision/Control Under Stochastic Uncertainty
  • 2. Deterministic Substitute Problems in Optimal Decision Under Stochastic Uncertainty
  • pt. II. Differentiation Methods
  • 3. Differentiation Methods for Probability and Risk Functions
  • pt. III. Deterministic Descent Directions
  • 4. Deterministic Descent Directions and Efficient Points
  • pt. IV. Semi-Stochastic Approximation Methods
  • 5. RSM-Based Stochastic Gradient Procedures
  • 6. Stochastic Approximation Methods with Changing Error Variances
  • pt. V. Reliability Analysis of Structures/Systems
  • 7. Computation of Probabilities of Survival/Failure by Means of Piecewise Linearization of the State Function
  • pt. VI. Appendix
  • A. Sequences, Series and Products
  • B. Convergence Theorems for Stochastic Sequences
  • C. Tools from Matrix Calculus.

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