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.
