TY  - RPRT
CY  - IIASA, Laxenburg, Austria
ID  - iiasa4089
UR  - https://pure.iiasa.ac.at/id/eprint/4089/
A1  - Rosa, C.H.
A1  - Ruszczynski, A.
Y1  - 1994/12//
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 and by decomposing it into nodes corresponding to stages. Theoretical convergence properties of the two approaches are derived and a computational illustration is presented.
PB  - WP-94-125
M1  - working_paper
TI  - On Augmented Lagrangian Decomposition Methods for Multistage Stochastic Programs
AV  - public
EP  - 23
ER  -