%0 Report
%9 IIASA Working Paper
%A Ruszczynski, A.
%C IIASA, Laxenburg, Austria
%D 1994
%F iiasa:4204
%T On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs
%U https://pure.iiasa.ac.at/id/eprint/4204/
%X A 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.