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Stochastic Optimization Algorithms and Applications [Hardcover]

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  • Category: Books (Mathematics)
  • ISBN-10:  0792369513
  • ISBN-10:  0792369513
  • ISBN-13:  9780792369516
  • ISBN-13:  9780792369516
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  448
  • Pages:  448
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Feb-2001
  • Pub Date:  01-Feb-2001
  • SKU:  0792369513-11-SPRI
  • SKU:  0792369513-11-SPRI
  • Item ID: 100891261
  • List Price: $219.99
  • Seller: ShopSpell
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  • Delivery by: Jul 04 to Jul 06
  • Notes: Brand New Book. Order Now.
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.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.Preface. Outlóä
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