Probabilistic Constrained Optimization Methodology and Applications
Probabilistic and percentile/quantile functions play an important role in several applications, such as finance (Value-at-Risk), nuclear safety, and the environment. Recently, significant advances have been made in sensitivity analysis and optimization of probabilistic functions, which is the basis...
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| Format: | eBook |
| Language: | English |
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New York, NY
Springer US
2000, 2000
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| Edition: | 1st ed. 2000 |
| Series: | Nonconvex Optimization and Its Applications
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- to the Theory of Probabilistic Functions and Percentiles
- Pricing American Options by Simulation Using a Stochastic Mesh with Optimized Weights
- On Optimization of Unreliable Material Flow Systems
- Stochastic Optimization in Asset & Liability Management: A Model for Non-Maturing Accounts
- Optimization in the Space of Distribution Functions and Applications in the Bayes Analysis
- Sensitivity Analysis of Worst-Case Distribution for Probability Optimization Problems
- On Maximum Reliability Problem in Parallel-Series Systems with Two Failure Modes
- Robust Monte Carlo Simulation for Approximate Covariance Matrices and VaR Analyses
- Structure of Optimal Stopping Strategies for American Type Options
- Approximation of Value-at-Risk Problems with Decision Rules
- Managing Risk with Expected Shortfall
- On the Numerical Solution of Jointly Chance Constrained Problems
- Management of Quality of Service through Chance-constraints in Multimedia Networks
- Solution of a Product Substitution Problem Using Stochastic Programming
- Some Remarks on the Value-at-Risk and the Conditional Value-at-Risk
- Statistical Inference of Stochastic Optimization Problems