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