Stochastic Optimization: Algorithms and Applications / Edition 1

Stochastic Optimization: Algorithms and Applications / Edition 1

ISBN-10:
0792369513
ISBN-13:
9780792369516
Pub. Date:
05/31/2001
Publisher:
Springer US
ISBN-10:
0792369513
ISBN-13:
9780792369516
Pub. Date:
05/31/2001
Publisher:
Springer US
Stochastic Optimization: Algorithms and Applications / Edition 1

Stochastic Optimization: Algorithms and Applications / Edition 1

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Overview

Shastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Shastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunications, and transportation. Recently, the practical experience gained in shastic programming has been expanded to a much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis. Major topics in this volume include: (1) advances in theory and implementation of shastic programming algorithms; (2) sensitivity analysis of shastic systems; (3) shastic programming applications and other related topics.
Audience: Researchers and academies working in optimization, computer modeling, operations research and financial engineering. The book is appropriate as supplementary reading in courses on optimization and financial engineering.

Product Details

ISBN-13: 9780792369516
Publisher: Springer US
Publication date: 05/31/2001
Series: Applied Optimization , #54
Edition description: 2001
Pages: 435
Product dimensions: 6.14(w) x 9.21(h) x 0.36(d)

Table of Contents

Output analysis for approximated shastic programs.- Combinatorial Randomized Rounding: Boosting Randomized Rounding with Combinatorial Arguments.- Statutory Regulation of Casualty Insurance Companies: An Example from Norway with Shastic Programming Analysis.- Option pricing in a world with arbitrage.- Monte Carlo Methods for Discrete Shastic Optimization.- Discrete Approximation in Quantile Problem of Portfolio Selection.- Optimizing electricity distribution using two-stage integer recourse models.- A Finite-Dimensional Approach to Infinite-Dimensional Constraints in Shastic Programming Duality.- Non—Linear Risk of Linear Instruments.- Multialgorithms for Parallel Computing: A New Paradigm for Optimization.- Convergence Rate of Incremental Subgradient Algorithms.- Transient Shastic Models for Search Patterns.- Value-at-Risk Based Portfolio Optimization.- Combinatorial Optimization, Cross-Entropy, Ants and Rare Events.- Consistency of Statistical Estimators: the Epigraphical View.- Hierarchical Sparsity in Multistage Convex Shastic Programs.- Conditional Value-at-Risk: Optimization Approach.
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