TY  - RPRT
CY  - IIASA, Laxenburg, Austria
ID  - iiasa4204
UR  - https://pure.iiasa.ac.at/id/eprint/4204/
A1  - Ruszczynski, A.
Y1  - 1994/02//
N2  - 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.
PB  - WP-94-005
M1  - working_paper
TI  - On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs
AV  - public
EP  - 8
ER  -