A decomposition approach in multistage stochastic programming

In this contribution we present a time and nodal decomposition approach to solve a rather general multistage stochastic programming problem that can be tackled in the framework of a discrete time optimal control problem. The optimal solution is obtained solving small decomposed subproblems and using a mean valued fixed-point iterative scheme. Moreover to enhance the convergence we propose an optimization step in which the weights are chosen in an optimal way at each iteration.