Introduction to stochastic programming
John R. Birge
Reading Time
at 250 WPM7h 28m
The average reader, reading at a speed of 250 WPM, would take 7h 28m to read Introduction to stochastic programming.
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448
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Introduction to stochastic programming
Published
Mar 17, 2013
Publisher
Springer
Pages
448
ISBN-13
9781475770834
ISBN-10
1475770839
Description
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.
Subjects
Stochastic models in operations research
Lectures on Stochastic Programming
Numerical techniques for stochastic optimization
Introduction to Stochastic Dynamic Programming
Stochastic programming
Stochastic programming 84
Frequently Asked Questions
How many pages are in Introduction to stochastic programming?
This edition of Introduction to stochastic programming has approximately 448 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Introduction to stochastic programming?
For most readers, Introduction to stochastic programming typically takes between 9h 20m and 6h 13m to complete. This is based on the book's length of approximately 112,000 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 7h 28m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 15 days • Estimated word count: 112,000 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Introduction to stochastic programming?
The estimated word count for Introduction to stochastic programming is approximately 112,000 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Introduction to stochastic programming?
Introduction to stochastic programming was written by John R. Birge.
When was Introduction to stochastic programming published?
The publication date for this specific edition is Mar 17, 2013. The original work may have been published on a different date.