Dynamic Stochastic Optimization / Edition 1

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Overview

This volume considers optimal shastic decision processes from the viewpoint of shastic programming. It focuses on theoretical properties and on approximate or numerical solution techniques for time-dependent optimization problems with random parameters (multistage shastic programs, optimal shastic decision processes). Methods for finding approximate solutions of probabilistic and expected cost based deterministic substitute problems are presented. Besides theoretical and numerical considerations, the proceedings volume contains selected refereed papers on many practical applications to economics and engineering: risk, risk management, portfolio management, finance, insurance-matters and control of robots.

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Product Details

  • ISBN-13: 9783540405061
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 1/12/2004
  • Series: Lecture Notes in Economics and Mathematical Systems Series , #532
  • Edition description: Softcover reprint of the original 1st ed. 2004
  • Edition number: 1
  • Pages: 336
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.72 (d)

Table of Contents

I. Dynamic Decision Problems under Uncertainty: Modeling Aspects.- Reflections on Output Analysis for Multistage Shastic Linear Programs.- Modeling Support for Multistage Recourse Problems.- Optimal Solutions for Undiscounted Variance Penalized Markov Decision Chains.- Approximation and Optimization for Shastic Networks.- II. Dynamic Shastic 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 Shastic Uncertainty.- Real-time Robust Optimal Trajectory Planning of Industrial Robots.- Adaptive Optimal Shastic Trajectory Planning and Control (AOSTPC) for Robots.- IV. Tools for Dynamic Shastic Optimization.- Solving Shastic Programming Problems by Successive Regression Approximations — Numerical Results.- Shastic 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.

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