Chance constraints are a major modeling tool for problems under uncertainty. We summarize the basic modeling ingredients of uncertain combinatorial problems and show how the Stochastic Constraint Satisfaction Problems formalism is able to support high-level declarative constructs that allow for ease of modeling of such problems in general. Then, we outline the different propagation methods for chance constraints. Finally, we identify some modeling subtleties that might arise when modeling with chance constraints.

中文翻译：

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利用机会约束对不确定性进行建模

机会约束是不确定性下问题的主要建模工具。我们总结了不确定的组合问题的基本建模要素，并说明了随机约束满足问题形式主义如何能够支持高级声明性构造，从而使此类问题的建模更为容易。然后，我们概述了机会约束的不同传播方法。最后，我们确定在具有机会约束的情况下进行建模时可能会出现的一些建模技巧。