Numerical Solution of Large-Scale Stochastic Programming Problems

研究大规模系统和计算方法的学科 它们的优化是具有许多应用的重要领域。 随机规划是这类研究中的一个重要领域。 本活动将侧重于开发随机 编程问题。 这里的大规模是指 约束以及决策和随机数 问题中的变量可能很大。 两个概率 （可靠性类型）约束和偏差惩罚是 融入到模型中。 随机变量是离散的 在某些模型中是连续的，在另一些模型中是随机的 在任何情况下都允许依赖。 在连续的情况下 分布随机变量多元数值积分 将使用近似技术。 可能的应用包括优化地震 抵抗结构，湖泊系统的水位调节， 互联电力系统的规划，经济， 财政和生产问题

The study of large-scale systems and methods of computing their optimizations is an important area with many applications. Stochastic Programming is an important area in such studies. This activity will focus on development of stochastic programming problems. Large scale here means the number of constraints as well as the number of decision and random variables in the problem can be large. Both probabilistic (reliability type) constraints and penalties for deviations are incorporated into the models. The random variables are discrete in some of the models and continuous in others but stochastic dependence is allowed in all cases. In the case of continuously distributed random variables a multivariate numerical integral approximation technique, will be used. Possible applications include optimization of earthquake resistant structures, water level regulation in lake systems, planning in interconnected power systems, solutions of economic, finance, production problems.