Lectures on Stochastic Programming - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Lectures on Stochastic Programming write by Alexander Shapiro. This book was released on 2009-01-01. Lectures on Stochastic Programming available in PDF, EPUB and Kindle. Optimization problems involving stochastic models occur in almost all areas of science and engineering, such as telecommunications, medicine, and finance. Their existence compels a need for rigorous ways of formulating, analyzing, and solving such problems. This book focuses on optimization problems involving uncertain parameters and covers the theoretical foundations and recent advances in areas where stochastic models are available. Readers will find coverage of the basic concepts of modeling these problems, including recourse actions and the nonanticipativity principle. The book also includes the theory of two-stage and multistage stochastic programming problems; the current state of the theory on chance (probabilistic) constraints, including the structure of the problems, optimality theory, and duality; and statistical inference in and risk-averse approaches to stochastic programming.
Lectures on Stochastic Programming: Modeling and Theory, Third Edition
Lectures on Stochastic Programming: Modeling and Theory, Third Edition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Lectures on Stochastic Programming: Modeling and Theory, Third Edition write by Alexander Shapiro. This book was released on 2021-08-19. Lectures on Stochastic Programming: Modeling and Theory, Third Edition available in PDF, EPUB and Kindle. An accessible and rigorous presentation of contemporary models and ideas of stochastic programming, this book focuses on optimization problems involving uncertain parameters for which stochastic models are available. Since these problems occur in vast, diverse areas of science and engineering, there is much interest in rigorous ways of formulating, analyzing, and solving them. This substantially revised edition presents a modern theory of stochastic programming, including expanded and detailed coverage of sample complexity, risk measures, and distributionally robust optimization. It adds two new chapters that provide readers with a solid understanding of emerging topics; updates Chapter 6 to now include a detailed discussion of the interchangeability principle for risk measures; and presents new material on formulation and numerical approaches to solving periodical multistage stochastic programs. Lectures on Stochastic Programming: Modeling and Theory, Third Edition is written for researchers and graduate students working on theory and applications of optimization, with the hope that it will encourage them to apply stochastic programming models and undertake further studies of this fascinating and rapidly developing area.
Lectures on Stochastic Programming
Lectures on Stochastic Programming - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Lectures on Stochastic Programming write by Alexander Shapiro. This book was released on 2014-07-09. Lectures on Stochastic Programming available in PDF, EPUB and Kindle. Optimization problems involving stochastic models occur in almost all areas of science and engineering, such as telecommunications, medicine, and finance. Their existence compels a need for rigorous ways of formulating, analyzing, and solving such problems. This book focuses on optimization problems involving uncertain parameters and covers the theoretical foundations and recent advances in areas where stochastic models are available. In Lectures on Stochastic Programming: Modeling and Theory, Second Edition, the authors introduce new material to reflect recent developments in stochastic programming, including: an analytical description of the tangent and normal cones of chance constrained sets; analysis of optimality conditions applied to nonconvex problems; a discussion of the stochastic dual dynamic programming method; an extended discussion of law invariant coherent risk measures and their Kusuoka representations; and in-depth analysis of dynamic risk measures and concepts of time consistency, including several new results.
Introduction to Stochastic Programming
Introduction to Stochastic Programming - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Stochastic Programming write by John R. Birge. This book was released on 2006-04-06. Introduction to Stochastic Programming available in PDF, EPUB and Kindle. This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.
Modeling with Stochastic Programming
Modeling with Stochastic Programming - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Modeling with Stochastic Programming write by Alan J. King. This book was released on 2012-06-19. Modeling with Stochastic Programming available in PDF, EPUB and Kindle. While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty. Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research at Lancaster University Management School in England.
