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Introduction to Stochastic Programming (Springer Series in Operations Research and Financial Engineering) - nuovo livro
2011, ISBN: 9781461402374
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2011, ISBN: 9781461402374
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2011, ISBN: 9781461402374
eBooks, eBook Download (PDF), Auflage, The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly… mais…
ISBN: 9781461402374
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 disciplin… mais…
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Introduction to Stochastic Programming (Springer Series in Operations Research and Financial Engineering) - nuovo livro
2011
ISBN: 9781461402374
Springer, Kindle Edition, Auflage: 2, 510 Seiten, Publiziert: 2011-06-15T00:00:00.000Z, Produktgruppe: Digital Ebook Purchas, Decision Making, Management Skills, Management, Business, Fin… mais…
ISBN: 9781461402374
*Introduction to Stochastic Programming* / pdf eBook für 63.99 € / Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik Medien > Bücher nein eBook als pdf eBooks > Fachthemen & … mais…
2011, ISBN: 9781461402374
eBooks, eBook Download (PDF), Auflage, [PU: Springer New York], [ED: 2], Springer New York, 2011
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Dados detalhados do livro - Introduction to Stochastic Programming
EAN (ISBN-13): 9781461402374
Ano de publicação: 2011
Editor/Editora: Springer New York
Livro na base de dados desde 2008-08-03T00:49:56-03:00 (Sao Paulo)
Página de detalhes modificada pela última vez em 2024-01-11T07:34:30-03:00 (Sao Paulo)
Número ISBN/EAN: 9781461402374
Número ISBN - Ortografia alternativa:
978-1-4614-0237-4
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: franco, louveau, lou, louv, franc, hackmann
Título do livro: stochastic
Dados da editora
Autor: John R. Birge; François Louveaux
Título: Springer Series in Operations Research and Financial Engineering; Introduction to Stochastic Programming
Editora: Springer; Springer US
485 Páginas
Ano de publicação: 2011-06-15
New York; NY; US
Língua: Inglês
64,19 € (DE)
66,00 € (AT)
71,00 CHF (CH)
Available
XXV, 485 p. 44 illus.
EA; E107; eBook; Nonbooks, PBS / Mathematik/Sonstiges; Unternehmensforschung; Verstehen; Stochastic optimization; Two-Stage Linear Recourse Problems; decision making under uncertainty; dynamic programming; C; Operations Research, Management Science; Statistics and Computing; Optimization; Mathematics and Statistics; Wahrscheinlichkeitsrechnung und Statistik; Mathematische und statistische Software; Optimierung; BB
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)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 Includes supplementary material: sn.pub/extras
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