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Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. N° de réf. du vendeur 00086824451
The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now 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 aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on 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.
In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods.The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest.
Review of First Edition:
"The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make 'Introduction to Stochastic Programming' an ideal textbook for the area." (Interfaces, 1998)
À propos de l?auteur: John R. Birge, is a Jerry W. and Carol Lee Levin Professor of Operations Management at the University of Chicago Booth School of Business. François Louveaux is a Professor at the University of Namur(FUNDP) in the Department of Business Administration
Titre : Introduction to Stochastic Programming (...
Éditeur : Springer
Date d'édition : 2011
Reliure : Couverture rigide
Etat : Good
Edition : 2ème Édition
Vendeur : thebookforest.com, San Rafael, CA, Etats-Unis
Etat : New. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped. N° de réf. du vendeur BAY_00_SH_021243
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Well-paced and wide-ranging introduction to this subject Prime goal is to help students develop an intuition on how to model uncertainty into mathematical problems Provides a first course in stochastic programming suitable for students. N° de réf. du vendeur 4196761
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Hardcover. Etat : Brand New. 2nd edition. 500 pages. 10.16x7.09x1.34 inches. In Stock. This item is printed on demand. N° de réf. du vendeur __1461402360
Quantité disponible : 2 disponible(s)
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now 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 aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on 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.In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods.The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest. Review of First Edition:'The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make 'Introduction to Stochastic Programming' an ideal textbook for the area.' (Interfaces, 1998) 485 pp. Englisch. N° de réf. du vendeur 9781461402367
Quantité disponible : 2 disponible(s)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar2716030035012
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 12694331-n
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 12694331-n
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now 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 aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on 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.In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods.The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest. Review of First Edition:'The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make 'Introduction to Stochastic Programming' an ideal textbook for the area.' (Interfaces, 1998). N° de réf. du vendeur 9781461402367
Quantité disponible : 2 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9781461402367
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Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Hardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1092. N° de réf. du vendeur C9781461402367
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