Linear Optimization is a powerful tool widely used to solve prescriptive analytics problems. However, for most real life problems, we may hardly convert them into specific linear optimization models where uncertainty exists. There are many different approaches to address the uncertainty, and stochastic optimization is one approach. Discuss the various conditions that we can use stochastic optimization to solve the optimal decisions and give one specific example to illustrate your arguments in detail. (20 marks)