Stochastic Optimization: Algorithms and Applications
By: edited by Stanislav Uryasev, Panos M. Pardalos
Contributors: Pardalos, Panos M.
Series: Applied Optimization -- 54; Applied Optimization -- 54
Publisher: Springer US
Published: 2001
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] /
Number of pages: 435
ISBN-13: 9781441948557; 9781475765946
Subjects: Mathematics; Mathematical optimization; Operations research; Electronic data processing
Description: 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.
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