Stochastic optimization (SO) methods are
optimization methods that generate and use
random variables. For stochastic problems, the random variables appear in the formulation of the optimization problem itself, which involve random
objective functions or random constraints, for example. Stochastic optimization methods also include methods with random iterates. Some stochastic optimization methods use random iterates to solve stochastic problems, combining both meanings of stochastic optimization. Stochastic optimization methods generalize
deterministic methods for deterministic problems.