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Stochastic Programming: Modeling Decision Problems Under Uncertainty (Graduate Texts in Operations Research) - Hardcover
Synopsis
This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book’s closing section, several case studies are presented, helping students apply the theory covered to practical problems.
The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide."synopsis" may belong to another edition of this title.
About the Author
Wim Klein Haneveld is Emeritus Professor in the Department of Operations at the University of Groningen. He is one of the pioneers of Stochastic Programming. He developed the Stochastic Programming course for graduate students at the University of Groningen and has taught this course for many years.
Maarten van der Vlerk was Professor in the Department of Operations at the University of Groningen. He was an expert in Stochastic Integer Programming. For many years he was lecturer of the Stochastic Programming course in Groningen and a PhD course on Stochastic Programming at the LNMB (the Dutch Network on the Mathematics of Operations Research).
Ward Romeijnders is Assistant Professor in the Department of Operations at the University of Groningen. He is an expert in Stochastic Integer Programming. He is the current lecturer of the Stochastic Programming courses in Groningen and at the LNMB.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2019
- ISBN 10 3030292185
- ISBN 13 9783030292188
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages261
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Stochastic Programming
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Springer Nature Switzerland, Springer International Publishing Nov 2019, 2019
ISBN 10: 3030292185
ISBN 13: 9783030292188
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book's closing section, several case studies are presented, helping students apply the theory covered to practical problems.The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide. 264 pp. Englisch. Seller Inventory # 9783030292188
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Stochastic Programming : Modeling Decision Problems Under Uncertainty
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Stochastic Programming
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a comprehensive course on stochastic programming on the graduate levelPlaces major emphasis on conceptual modelingShows students how to integrate risk in a linear programming framework. Seller Inventory # 334318814
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Stochastic Programming : Modeling Decision Problems Under Uncertainty
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book's closing section, several case studies are presented, helping students apply the theory covered to practical problems.The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide. Seller Inventory # 9783030292188
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Stochastic Programming: Modeling Decision Problems Under Uncertainty (Graduate Texts in Operations Research)
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