Modeling with Stochastic Programming (2nd ed.)

This is an updated version of what is still the only text to address basic questions about how to  model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This second edition has important extensions regarding  how to represent random phenomena in the models (also called scenario generation) as well as a new chapter on multi-stage models. This text would be suitable as a stand-alone