Stochastic Optimization -

Stochastic Optimization

Algorithms and Applications
Buch | Softcover
435 Seiten
2010 | Softcover reprint of hardcover 1st ed. 2001
Springer-Verlag New York Inc.
978-1-4419-4855-7 (ISBN)
213,99 inkl. MwSt
Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Recently, the practical experience gained in stochastic programming has been expanded to a much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis.
Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic 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 stochastic 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 stochastic programming algorithms; (2) sensitivity analysis of stochastic systems; (3) stochastic 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.

Output analysis for approximated stochastic programs.- Combinatorial Randomized Rounding: Boosting Randomized Rounding with Combinatorial Arguments.- Statutory Regulation of Casualty Insurance Companies: An Example from Norway with Stochastic Programming Analysis.- Option pricing in a world with arbitrage.- Monte Carlo Methods for Discrete Stochastic 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 Stochastic Programming Duality.- Non—Linear Risk of Linear Instruments.- Multialgorithms for Parallel Computing: A New Paradigm for Optimization.- Convergence Rate of Incremental Subgradient Algorithms.- Transient Stochastic 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 Stochastic Programs.- Conditional Value-at-Risk: Optimization Approach.

Erscheint lt. Verlag 1.12.2010
Reihe/Serie Applied Optimization ; 54
Zusatzinfo XII, 435 p.
Verlagsort New York, NY
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Technik Elektrotechnik / Energietechnik
Technik Maschinenbau
Wirtschaft Betriebswirtschaft / Management Finanzierung
ISBN-10 1-4419-4855-4 / 1441948554
ISBN-13 978-1-4419-4855-7 / 9781441948557
Zustand Neuware
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