Stochastic linear programming - Info and Reading Options
models, theory, and computation
By Peter Kall
"Stochastic linear programming" was published by Springer in 2005 - New York, it has 397 pages and the language of the book is English.
“Stochastic linear programming” Metadata:
- Title: Stochastic linear programming
- Author: Peter Kall
- Language: English
- Number of Pages: 397
- Publisher: Springer
- Publish Date: 2005
- Publish Location: New York
“Stochastic linear programming” Subjects and Themes:
- Subjects: ➤ Stochastic processes - Linear programming - Programmation linéaire - Processus stochastiques - 31.80 applications of mathematics - Lineare Optimierung - Operations Research - Stochastik - Stochastische Optimierung - Lineaire programmering - Stochastische processen - Economie - Programació lineal - Processos estocàstics - Distribution (Probability theory) - Engineering mathematics - Mathematical optimization - Mathematics
Edition Specifications:
- Pagination: p. cm.
Edition Identifiers:
- The Open Library ID: OL3312302M - OL3039532W
- Online Computer Library Center (OCLC) ID: 57392269
- Library of Congress Control Number (LCCN): 2004066228
- ISBN-13: 9780387233857
- ISBN-10: 0387233857
- All ISBNs: 0387233857 - 9780387233857
AI-generated Review of “Stochastic linear programming”:
"Stochastic linear programming" Description:
The Open Library:
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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