Dynamic Stochastic Optimization
Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant ris...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2004, 2004
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| Edition: | 1st ed. 2004 |
| Series: | Lecture Notes in Economics and Mathematical Systems
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- I. Dynamic Decision Problems under Uncertainty: Modeling Aspects
- Reflections on Output Analysis for Multistage Stochastic Linear Programs
- Modeling Support for Multistage Recourse Problems
- Optimal Solutions for Undiscounted Variance Penalized Markov Decision Chains
- Approximation and Optimization for Stochastic Networks
- II. Dynamic Stochastic Optimization in Finance
- Optimal Stopping Problem and Investment Models
- Estimating LIBOR/Swaps Spot-Volatilities: the EpiVolatility Model
- Structured Products for Pension Funds
- III. Optimal Control Under Stochastic Uncertainty
- Real-time Robust Optimal Trajectory Planning of Industrial Robots
- Adaptive Optimal Stochastic Trajectory Planning and Control (AOSTPC) for Robots
- IV. Tools for Dynamic Stochastic Optimization
- Solving Stochastic Programming Problems by Successive Regression Approximations — Numerical Results
- Stochastic Optimization of Risk Functions via Parametric Smoothing
- Optimization under Uncertainty using Momentum
- Perturbation Analysis of Chance-constrained Programs under Variation of all Constraint Data
- The Value of Perfect Information as a Risk Measure
- New Bounds and Approximations for the Probability Distribution of the Length of the Critical Path
- Simplification of Recourse Models by Modification of Recourse Data