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Probabilistic Constrained Optimization

Methodology and Applications

  • Book
  • © 2000

Overview

Editors:
  1. Stanislav P. Uryasev

    1. University of Florida, Gainesville, USA

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Part of the book series: Nonconvex Optimization and Its Applications (NOIA, volume 49)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Introduction to the Theory of Probabilistic Functions and Percentiles (Value-at-Risk)

    • S. Uryasev
    Pages 1-25

  3. Pricing American Options by Simulation Using a Stochastic Mesh with Optimized Weights

    • Mark Broadie, Paul Glasserman, Zachary Ha
    Pages 26-44

  4. On Optimization of Unreliable Material Flow Systems

    • Yu. Ermoliev, S. Uryasev, J. Wessels
    Pages 45-66

  5. Stochastic Optimization in Asset & Liability Management: A Model for Non-Maturing Accounts

    • Karl Frauendorfer, Michael Schürle
    Pages 67-101

  6. Optimization in the Space of Distribution Functions and Applications in the Bayes Analysis

    • Alexandr N. Golodnikov, Pavel S. Knopov, Panos M. Pardalos, Stanislav P. Uryasev
    Pages 102-131

  7. Sensitivity Analysis of Worst-Case Distribution for Probability Optimization Problems

    • Yu. S. Kan, A. I. Kibzun
    Pages 132-147

  8. On Maximum Reliability Problem in Parallel-Series Systems with Two Failure Modes

    • Vladimir Kirilyuk
    Pages 148-159

  9. Robust Monte Carlo Simulation for Approximate Covariance Matrices and VaR Analyses

    • Alexander Kreinin, Alexander Levin
    Pages 160-172

  10. Structure of Optimal Stopping Strategies for American Type Options

    • Alexander G. Kukush, Dmitrii S. Silvestrov
    Pages 173-185

  11. Approximation of Value-at-Risk Problems with Decision Rules

    • Riho Lepp
    Pages 186-197

  12. Managing Risk with Expected Shortfall

    • Helmut Mausser, Dan Rosen
    Pages 198-219

  13. On the Numerical Solution of Jointly Chance Constrained Problems

    • János Mayer
    Pages 220-235

  14. Management of Quality of Service through Chance-constraints in Multimedia Networks

    • E. A. Medova, J. E. Scott
    Pages 236-251

  15. Solution of a Product Substitution Problem Using Stochastic Programming

    • Michael R. Murr, András Prékopa
    Pages 252-271

  16. Some Remarks on the Value-at-Risk and the Conditional Value-at-Risk

    • Georg Ch. Pflug
    Pages 272-281

  17. Statistical Inference of Stochastic Optimization Problems

    • Alexander Shapiro
    Pages 282-307
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Keywords

About this book

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 for construction of new efficient approaches. This book presents the state of the art in the theory of optimization of probabilistic functions and several engineering and finance applications, including material flow systems, production planning, Value-at-Risk, asset and liability management, and optimal trading strategies for financial derivatives (options).
Audience: The book is a valuable source of information for faculty, students, researchers, and practitioners in financial engineering, operation research, optimization, computer science, and related areas.

Reviews

`It can be recommened to graduate students, researchers and practitioners in operation research and financial decision-making problems.'
Mathematical Reviews, 2002a

Editors and Affiliations

  • University of Florida, Gainesville, USA

    Stanislav P. Uryasev

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