Combinatorial optimisation problems often contain uncertainty that has to be taken into account to produce realistic solutions. However, existing modelling systems either do not support uncertainty, or do not support combinatorial features, such as integer variables and non-linear constraints. This paper presents an extension of the MINIZINC modelling language that supports uncertainty. Stochas...