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Introduction To Stochastic Programming (97 Edition)

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Introduction To Stochastic Programming (97 Edition) Cover

 

Synopses & Reviews

Please note that used books may not include additional media (study guides, CDs, DVDs, solutions manuals, etc.) as described in the publisher comments.

Publisher Comments:

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. 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 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. The first chapters introduce some worked examples of stochastic programming and demonstrate how a stochastic model is formally built. Subsequent chapters develop the properties of stochastic programs and the basic solution techniques used to solve them. Three chapters cover approximation and sampling techniques and the final chapter presents a case study in depth. A wide range of students from operations research, industrial engineering, and related disciplines will find this a well-paced and wide-ranging introduction to this subject.

Description:

Includes bibliographical references (p. [387]-410) and indexes.

Table of Contents

I Models * Introduction and Examples * Uncertainty and Modeling Issues * II Basic Properties * Basic Properties and Theory * The Value of Information and the Stochastic Solution * III Solution Methods * Two-Stage Linear Recourse Problems * Nonlinear Programming Approaches to Two-Stage Recourse Problems * Multistage Stochastic Programs * Stochastic Integer Programs * IV Approximation and Sampling Methods * Evaluating and Approximating Expectations * Monte Carlo Methods * Multistage Approximations * V A Case Study * Capacity Expansion * Appendix: Sample Distribution Functions

Product Details

ISBN:
9780387982175
Author:
Birge, John R.
Author:
Louveaux, Francois
Author:
Louveaux, Franaois
Author:
Louveaux, Franois
Author:
Birge, John R.
Publisher:
Springer
Location:
New York :
Subject:
Linear Programming
Subject:
Programming - General
Subject:
Probability
Subject:
Operations Research
Subject:
Programming (Mathematics)
Subject:
Stochastic programming.
Subject:
Probability & Statistics - General
Subject:
Operations Research/Decision Theory
Subject:
Software Engineering - Programming and Languages
Copyright:
Edition Number:
1
Edition Description:
1997. Corr. 2nd
Series:
Springer Series in Operations Research and Financial Engineering
Series Volume:
8001
Publication Date:
19970718
Binding:
HARDCOVER
Language:
English
Illustrations:
Y
Pages:
448
Dimensions:
235 x 155 mm 1770 gr

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Related Subjects

Computers and Internet » Software Engineering » Programming and Languages
Science and Mathematics » Mathematics » Computer
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

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