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Chance Constrained and Monte Carlo Modeling

In: Public Systems Modeling

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  • Daniel P. Loucks

    (Cornell University)

Abstract

Constraints of models that contain random variables may be applicable only some of the time. Constraints that apply only a specified fraction of the time are called chance constraints. This chapter illustrates how chance constraints can be included in optimization models. In addition, the chapter demonstrates how to generate values of random variables fitting user defined probability distributions. These random variable values often serve as inputs to stochastic simulation models.

Suggested Citation

  • Daniel P. Loucks, 2022. "Chance Constrained and Monte Carlo Modeling," International Series in Operations Research & Management Science, in: Public Systems Modeling, chapter 0, pages 177-185, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-93986-1_14
    DOI: 10.1007/978-3-030-93986-1_14
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