Stochastic and Chance-Constrained Programming

An introduction to stochastic mathematical programming formulations will be given. Scenario-based approximations and sample-based estimations will be discussed as approaches to solving such problems. An example of a habitat restoration model that is discrete in both time and space will be presented.

Michael Bevers, USDA

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