Werner Römisch,
Rüdiger Schultz
Preprint series:
Institut für Mathematik, Humboldt-Universität zu Berlin (ISSN 0863-0976)
MSC 2000
- 90C15 Stochastic programming
Abstract
We consider linear multistage stochastic integer programs and
study their functional and dynamic programming formulations as
well as conditions for optimality and stability of solutions.
Furthermore, we study the application of the Rockafellar-Wets
dualization approach as well as the structure and algorithmic
potential of corresponding dual problems. For discrete underlying
probability distributions we discuss possible large scale
mixed-integer linear programming formulations and three dual
decomposition approaches, namely, scenario, component
and nodal decomposition.
Keywords:
stochastic programming, multistage, mixed-integer, dynamic programming, dualization, decomposition