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."Sinopsis" puede pertenecer a otra edición de este libro.
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.
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: Mooney's bookstore, Den Helder, Holanda
Condición: Very good. Nº de ref. del artículo: E-9783030292188-6-2
Cantidad disponible: 1 disponibles
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
Condición: new. Questo è un articolo print on demand. Nº de ref. del artículo: defef33ed5226a4abe7133908b0308af
Cantidad disponible: Más de 20 disponibles
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9783030292188_new
Cantidad disponible: Más de 20 disponibles
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Buch. Condición: 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. Nº de ref. del artículo: 9783030292188
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Condición: 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. Nº de ref. del artículo: 334318814
Cantidad disponible: Más de 20 disponibles
Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. pp. XII, 249 27 illus., 1 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP. Nº de ref. del artículo: 26384555805
Cantidad disponible: 4 disponibles
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condición: New. Nº de ref. del artículo: V9783030292188
Cantidad disponible: 15 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand pp. XII, 249 27 illus., 1 illus. in color. Nº de ref. del artículo: 379348162
Cantidad disponible: 4 disponibles
Librería: Biblios, Frankfurt am main, HESSE, Alemania
Condición: New. PRINT ON DEMAND pp. XII, 249 27 illus., 1 illus. in color. Nº de ref. del artículo: 18384555799
Cantidad disponible: 4 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 264 pp. Englisch. Nº de ref. del artículo: 9783030292188
Cantidad disponible: 1 disponibles