Parallel Processors for Planning Under Uncertainty

G. B. Dantzig and P. W. Glynn

Annals of Operations Research, Vol. 22, 1-21 (1990)

Our goal is to demonstrate for an important class of multistage stochastic models that three techniques — namely nested decomposition, Monte Carlo importance sampling, and parallel computing — can be effectively combined to solve this fundamental problem of large-scale linear programming.