Stochastic Linear Programming: Models, Theory, and Computation (International Series in Operations Research & Management Science)

Kall, Peter; Mayer, János

ISBN 10: 0387233857 / ISBN 13: 9780387233857

Published by Springer, 2005

About this Item

Seller Inventory # ABE-1777463748296

Bibliographic Details

• Title: Stochastic Linear Programming: Models, Theory, and Computation (International Series in Operations Research & Management Science)
• Publisher: Springer
• Publication Date: 2005
• Language: English
• ISBN 10: 0387233857
• ISBN 13: 9780387233857
• Binding: Hardcover
• Edition: 1st Edition
• Condition: Fine
• Dimensions: 2.54W x 15.88H x 24.13D centimeters 2.54 centimeters width by 15.88 centimeters height by 24.13 centimeters depth
• Weight: 839 grams

About this title

Synopsis

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.

From the Back Cover

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.