Title:
Decomposition Methods in Stochastic Programming
Author:
Andrzej Ruszczynski
Session:
MO-pm-SPO
Keywords:
stochastic programming, decomposition
Abstract:
Stochastic programming problems have very large dimension and
special structures which are tractable by decomposition.
We review basic ideas of cutting plane
methods, augmented Lagrangian and splitting methods,
and stochastic decomposition methods
for convex polyhedral multi-stage stochastic programming problems.