Stochastic optimization

This article is about iterative methods. For the modeling (and optimization) of decisions under uncertainty, see stochastic programming. For the context of control theory, see stochastic control.

Stochastic optimization (SO) are optimization methods that generate and use random variables. For stochastic optimization problems, the objective functions or constraints are random. Stochastic optimization also include methods with random iterates. Some hybrid methods use random iterates to solve stochastic problems, combining both meanings of stochastic optimization.[1] Stochastic optimization methods generalize deterministic methods for deterministic problems.

  1. ^ Spall, J. C. (2003). Introduction to Stochastic Search and Optimization. Wiley. ISBN 978-0-471-33052-3.