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Modeling with Stochastic Programming

  • Textbook
  • © 2012

Overview

Authors:
  1. Alan J. King

    1. T.J. Watson Research Center, IBM Corporation, Yorktown Heights, USA

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  2. Stein W. Wallace

    1. Lancaster University, Lancaster, United Kingdom

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    You can also search for this author in PubMed   Google Scholar

  • The first and only book discussing how to model stochastic programs
  • Mostly non-technical and focuses on the concepts
  • Written by two of the key international researchers
  • Includes supplementary material: sn.pub/extras

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Uncertainty in Optimization

    • Alan J. King, Stein W. Wallace
    Pages 1-31

  3. Modeling Feasibility and Dynamics

    • Alan J. King, Stein W. Wallace
    Pages 33-60

  4. Modeling the Objective Function

    • Alan J. King, Stein W. Wallace
    Pages 61-76

  5. Scenario-Tree Generation: With Michal Kaut

    • Alan J. King, Stein W. Wallace
    Pages 77-102

  6. Service Network Design: With Arnt-Gunnar Lium and Teodor Gabriel Crainic

    • Alan J. King, Stein W. Wallace
    Pages 103-122

  7. A Multidimensional Newsboy Problem with Substitution: With Hajnalka Vaagen

    • Alan J. King, Stein W. Wallace
    Pages 123-138

  8. Stochastic Discount Factors

    • Alan J. King, Stein W. Wallace
    Pages 139-152

  9. Long Lead Time Production: With Aliza Heching

    • Alan J. King, Stein W. Wallace
    Pages 153-164

  10. Back Matter

    Pages 165-173
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Keywords

About this book

While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty. Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research at Lancaster University Management School in England.

Reviews

From the reviews:

“It is the first book that systematically tries to answer the questions about modeling under uncertainty … . The book is written in a very readable style … . An experienced researcher who is already familiar with optimization under uncertainty will benefit from reading this book … .” (Laura Galli, Interfaces, Vol. 43 (5), September-October, 2013)

“The book is intended as a textbook for graduate students and researchers interested in decision making under uncertainty. It is expected that the book will also be suitable for teaching some operations research courses for undergraduates. … this textbook can indeed be very useful for mathematics students as a methodological guide to the applications of stochastic programming methods. The structure of the textbook is well adapted to teaching purposes.” (A. H. Žilinskas, Mathematical Reviews, January, 2013)

Authors and Affiliations

  • T.J. Watson Research Center, IBM Corporation, Yorktown Heights, USA

    Alan J. King

  • Lancaster University, Lancaster, United Kingdom

    Stein W. Wallace

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