Language Constructs for Modeling Stochastic Linear Programs

Robert Entriken ()

Annals of Operations Research, 2001, vol. 104, issue 1, 49-66

Abstract: This paper introduces two tokens of syntax for algebraic modeling languages that are sufficient to model a wide variety of stochastic optimization problems. The tokens are used to declare random parameters and to define a precedence relationship between different random events. It is necessary to make a number of assumptions in order to use this syntax, and it is through these assumptions, which cover the areas of model structure, time, replication, and stages, that we can attain a deeper understanding of this class of problem. Copyright Kluwer Academic Publishers 2001

Date: 2001
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DOI: 10.1023/A:1013182717628

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