Modelling support for stochastic programs

In many decision problems, some of the factors considered are subject to significant uncertainty, randomness, or statistical fluctuations: these circumstances motivate the study of stochastic models. The paper is intended to provide an overview of modelling tools available for the development, analysis, solution and maintenance of stochastic programs. A brief introduction to some important model forms is followed by a review of suitable modelling and computational environments, including algebraic modelling languages. Aspects of problem description, solution methodology, report generation, and visual problem representation, as well as certain auxiliary tools and diagnostics are discussed. An extensive list of references is provided, to give further pointers into a challenging field of great practical importance.