Modeling with Stochastic Programming

  • Alan J. King
  • Stein W. Wallace

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Alan J. King, Stein W. Wallace
    Pages 1-31
  3. Alan J. King, Stein W. Wallace
    Pages 33-60
  4. Alan J. King, Stein W. Wallace
    Pages 61-76
  5. Alan J. King, Stein W. Wallace
    Pages 77-102
  6. Alan J. King, Stein W. Wallace
    Pages 139-152
  7. Alan J. King, Stein W. Wallace
    Pages 153-164
  8. Back Matter
    Pages 165-173

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.



Real Options Modeling Stochastic Discount Factors Stochastic programming formulation Uncertainty in Optimization

Authors and affiliations

  • Alan J. King
    • 1
  • Stein W. Wallace
    • 2
  1. 1.T.J. Watson Research CenterIBM CorporationYorktown HeightsUSA
  2. 2.Lancaster UniversityLancasterUnited Kingdom

Bibliographic information

Industry Sectors
Finance, Business & Banking
IT & Software
Energy, Utilities & Environment
Oil, Gas & Geosciences