RT Monograph
SR 00
A1 Rosa, C.H.
A1 Ruszczynski, A.
T1 On Augmented Lagrangian Decomposition Methods for Multistage Stochastic Programs
YR 1994
FD 1994-12
SP 23
AB 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
PP IIASA, Laxenburg, Austria
AV Published
LK https://pure.iiasa.ac.at/id/eprint/4089/