Stochastic Linear Programming Models, Theory , And Computation
- 2nd ed.
- New York : Springer, 2011
- xx, 426 p. ; ill., 25 cm
- International series in operations research & management science .
Includes bibliographical references and index.
Stochastic Linear Programming: Models, Theory, and Computation is a 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." "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.
9781071605134
Random variables Probability distribution Moment problem Convex optimization SLP Models Optimization problems Operations Research Financial Optimization