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Basic Properties and Theory

  • John R. BirgeEmail author
  • François Louveaux
Chapter
Part of the Springer Series in Operations Research and Financial Engineering book series (ORFE)

Abstract

This chapter considers the basic properties and theory of stochastic programming. As throughout this book, the emphasis is on results that have direct application in the solution of stochastic programs. Proofs are included for those results we consider most central to the overall development.

Keywords

Valid Inequality Probabilistic Constraint Discrete Random Variable Continuous Random Variable Chance Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Booth School of BusinessUniversity of ChicagoChicagoUSA
  2. 2.Department of Business AdministrationUniversity of NamurNamurBelgium

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