中文摘要：

概率约束最优化问题是随机规划的一类重要问题，在金融、管理和工程计划等领域有广泛的应用．概率约束优化问题近年来受到了广泛的关注和重视，在应用建模、理论和方法等方面取得了不少重要的进展。这里主要概述和总结处理概率约束的主要方法和思想，包括凸内逼近方法、情景逼近方法、DC方法和整数规划方法等，并对概率约束最优化的研究前景进行讨论．

英文摘要：

We give a brief review on the probabilistically constrained optimization problem which is an important class of stochastic programming with wide applications in finance, management and engineering planning. We introduce the modeling of prob- abilistic constraints and summarize some important solution methods including convex approximation, DC approach, scenario approach and integer programming approach. We also discuss some future research perspectives of the probabilistically constrained opti- mization problem.