Stochastic Linear Programming

Name: Stochastic Linear Programming
Brand: Springer, Berlin
SKU: 9781441936219
Price: 428.83 PLN
Availability: InStock

Models, Theory, and Computation

Autor: Peter Kall, János Mayer

Język:

Oprawa: Miękka

Wydawca: Springer, Berlin

Dostępność: 50 % szansa

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428.83 zł

Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and thei...

Informacje o książce

Autor

Peter Kall, János Mayer

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2010

strony

398

EAN

9781441936219

Enbook ID

01422207

Wydawca

Springer, Berlin

Wymiary

155 x 235 x 21

Pełny opis

Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization. Stochastic Linear Programming is a definitive presentation and discussion of the theoretical properties of the models, the conceptual algorithmic approaches, and the computational issues relating to the implementation of these methods to solve problems that are stochastic in nature.Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization. STOCHASTIC LINEAR PROGRAMMING: Models, Theory, and Computation is a definitive presentation and discussion of the theoretical properties of the models, the conceptual algorithmic approaches, and the computational issues relating to the implementation of these methods to solve problems that are stochastic in nature. The application area of stochastic programming includes portfolio analysis, financial optimization, energy problems, random yields in manufacturing, risk analysis, etc. In this book models in financial optimization and risk analysis are discussed as examples, including solution methods and their implementation.§Stochastic programming is a fast developing area of optimization and mathematical programming. Numerous papers and conference volumes, and several monographs have been published in the area; however, the Kall & Mayer book will be particularly useful in presenting solution methods including their solid theoretical basis and their computational issues, based in many cases on implementations by the authors. The book is also suitable for advanced courses in stochastic optimization.

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Stochastic Linear Programming

Models, Theory, and Computation

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