Also known as: Stochastic Optimisation
Stochastic optimization refers to optimization methods that involve randomness in the objective, constraints, sampling, or search process. It is used when problems contain uncertainty or when random sampling makes large optimization problems more tractable.
Any optimization method that generates and uses random variables. For stochastic problems, the random variables appear in the formulation of the optimization problem itself, which involves random objective functions or random constraints. 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.