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Stochastic Linear Programming

Chapter
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Part of the International Series in Operations Research & Management Science book series (ISOR, volume 203)

Abstract

In this chapter, after overviewing elementary probability, two-stage programming and chance constrained programming are explained in detail. In two-stage programming, a shortage or an excess arising from the violation of the constraints is penalized, and then the expectation of the amount of the penalties for the constraint violation is minimized. In contrast, chance constrained programming admits random data variations and permits constraint violations up to specified probability limits, and its formulation is somewhat variable, including the expectation model, the variance model, the probability model, and the fractile model.

Keywords

Objective Function Linear Programming Problem Normal Random Variable Expectation Model 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 New York 2013

Authors and Affiliations

  1. 1.Department of System Cybernetics Graduate School of EngineeringHiroshima UniversityHigashi-HiroshimaJapan
  2. 2.Department of Social Sciences Graduate School of Humanities and Social SciencesNagoya City UniversityNagoyaJapan

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