Stochastic optimization is a leading approach to model optimization problemsrnin which there is uncertainty in the input data, whether from measurementrnnoise or an inability to know the future. This paper focuses onrntypes of Stochastic optimization such as Stochastic optimization problemsrnwith recourse and Chance constrained optimization problems as well as howrnto change one Stochastic optimization problems to deterministic equivalentrnform.rnKeywords: Probability, Random Variable, Expected value, Measure, Convex,rnStochastic Optimization, Recourse, Chance Constrained