Lectures on Stochastic Programming

Lectures on Stochastic Programming
Author: Alexander Shapiro
Publisher: SIAM
Total Pages: 447
Release: 2009-01-01
Genre: Mathematics
ISBN: 0898718759

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.

Introduction to Stochastic Programming

Introduction to Stochastic Programming
Author: John R. Birge
Publisher: Springer Science & Business Media
Total Pages: 427
Release: 2006-04-06
Genre: Mathematics
ISBN: 0387226184

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.

Applications of Stochastic Programming

Applications of Stochastic Programming
Author: Stein W. Wallace
Publisher: SIAM
Total Pages: 724
Release: 2005-01-01
Genre: Mathematics
ISBN: 9780898718799

Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.

Lectures on Stochastic Programming

Lectures on Stochastic Programming
Author: Alexander Shapiro
Publisher: SIAM
Total Pages: 512
Release: 2014-07-09
Genre: Mathematics
ISBN: 1611973430

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.

Stochastic Programming: Applications In Finance, Energy, Planning And Logistics

Stochastic Programming: Applications In Finance, Energy, Planning And Logistics
Author: Horand I Gassmann
Publisher: World Scientific
Total Pages: 549
Release: 2012-11-28
Genre: Business & Economics
ISBN: 9814407526

This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems./a

Multistage Stochastic Optimization

Multistage Stochastic Optimization
Author: Georg Ch. Pflug
Publisher: Springer
Total Pages: 309
Release: 2014-11-12
Genre: Business & Economics
ISBN: 3319088432

Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.

Transmission Expansion Planning: The Network Challenges of the Energy Transition

Transmission Expansion Planning: The Network Challenges of the Energy Transition
Author: Sara Lumbreras
Publisher: Springer Nature
Total Pages: 311
Release: 2020-11-19
Genre: Technology & Engineering
ISBN: 3030494284

This book presents a panoramic look at the transformation of the transmission network in the context of the energy transition. It provides readers with basic definitions as well as details on current challenges and emerging technologies. In-depth chapters cover the integration of renewables, the particularities of planning large-scale systems, efficient reduction and solution methods, the possibilities of HVDC and super grids, distributed generation, smart grids, demand response, and new regulatory schemes. The content is complemented with case studies that highlight the importance of the power transmission network as the backbone of modern energy systems. This book will be a comprehensive reference that will be useful to both academics and practitioners.

Continuous Optimization

Continuous Optimization
Author: V. Jeyakumar
Publisher: Springer Science & Business Media
Total Pages: 476
Release: 2005-08-10
Genre: Business & Economics
ISBN: 9780387267692

The search for the best possible performance is inherent in human nature. Individuals, enterprises and governments all seek optimal—that is, the best—possible solutions of problems that they meet. Evidently, continuous optimization plays an increasingly significant role in everyday management and technical decisions in science, engineering and commerce. The collection of 16 refereed papers in this book covers a diverse number of topics and provides a good picture of recent research in continuous optimization. The first part of the book presents substantive survey articles in a number of important topic areas of continuous optimization. Most of the papers in the second part present results on the theoretical aspects as well as numerical methods of continuous optimization. The papers in the third part are mainly concerned with applications of continuous optimization. Hence, the book will be an additional valuable source of information to faculty, students, and researchers who use continuous optimization to model and solve problems. Audience This book is intended for researchers in mathematical programming, optimization and operations research; engineers in various fields; and graduate students in applied mathematics, engineering and operations research.

Stochastic Linear Programming

Stochastic Linear Programming
Author: Peter Kall
Publisher: Springer Science & Business Media
Total Pages: 439
Release: 2010-11-02
Genre: Mathematics
ISBN: 1441977295

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. ... The presentation includes geometric interpretation, linear programming duality, and the simplex method in its primal and dual forms. ... The authors have made an effort to collect ... the most useful recent ideas and algorithms in this area. ... A guide to the existing software is included as well." (Darinka Dentcheva, Mathematical Reviews, Issue 2006 c) "This is a graduate text in optimisation whose main emphasis is in stochastic programming. The book is clearly written. ... This is a good book for providing mathematicians, economists and engineers with an almost complete start up information for working in the field. I heartily welcome its publication. ... It is evident that this book will constitute an obligatory reference source for the specialists of the field." (Carlos Narciso Bouza Herrera, Zentralblatt MATH, Vol. 1104 (6), 2007)

Stochastic Programming

Stochastic Programming
Author: RUSZCZYNSK
Publisher: North Holland
Total Pages: 708
Release: 2003-10-09
Genre: Business & Economics
ISBN:

Brings together leading in the most important sub-fields of stochastic programming to present a rigourous overview of basic models, methods and applications of stochastic programming. The text is intended for researchers, students, engineers and economists, who encounter in their work optimization problems involving uncertainty.