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Item Details
| Title:
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STOCHASTIC LINEAR PROGRAMMING
MODELS, THEORY, AND COMPUTATION |
| By: |
Peter Kall, Janos Mayer |
| Format: |
Hardback |
| List price:
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£82.50 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
0387233857 |
| ISBN 13: |
9780387233857 |
| Publisher: |
SPRINGER-VERLAG NEW YORK INC. |
| Pub. date: |
17 February, 2005 |
| Edition: |
and ed. |
| Series: |
International Series in Operations Research & Management Science v. 80 |
| Pages: |
416 |
| Description: |
Presents 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. This book includes portfolio analysis, financial optimization, energy problems, random yields in manufacturing, and risk analysis. |
| Synopsis: |
Peter Kall and Janos 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 and 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. |
| Illustrations: |
32 black & white illustrations, 2 black & white tables |
| Publication: |
US |
| Imprint: |
Springer-Verlag New York Inc. |
| Returns: |
Non-returnable |
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