| Article ID: | iaor1990297 |
| Country: | Switzerland |
| Volume: | 22 |
| Start Page Number: | 1 |
| End Page Number: | 21 |
| Publication Date: | Jan 1990 |
| Journal: | Annals of Operations Research |
| Authors: | Glynn Peter W., Dantzig George B. |
The present 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.