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Language Constructs for Modeling Stochastic Linear Programs

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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.

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Authors and Affiliations

  1. EPRI, 3412 Hilview Avenue, Palo Alto, CA, 94304-0813, USA

    Robert Entriken

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  1. Robert Entriken
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Entriken, R. Language Constructs for Modeling Stochastic Linear Programs. Annals of Operations Research 104, 49–66 (2001). https://doi.org/10.1023/A:1013182717628

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  • DOI: https://doi.org/10.1023/A:1013182717628

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