On Augmented Lagrangian Decomposition Methods For Multistage Stochastic ProgramsA.RuszczynskiauthorA general decomposition framework for large convex optimization problems based on augmented Lagrangians is described. The approach is then applied to multistage stochastic programming problems in two different ways: by decomposing the problem into scenarios or decomposing it into nodes corresponding to stages. In both cases the method has favorable convergence properties and a structure which makes it convenient for parallel computing environments.1994-02WP-94-005Monograph