| Article ID: | iaor19951122 |
| Country: | United States |
| Volume: | 24 |
| Issue: | 5 |
| Start Page Number: | 857 |
| End Page Number: | 871 |
| Publication Date: | May 1993 |
| Journal: | International Journal of Systems Science |
| Authors: | Sengupta J.K. |
| Keywords: | neural networks, programming: linear |
A class of non-parametric methods based on the minimax solution is developed here for models of stochastic linear programming. These methods povide a measure of robustness through the adoption of a cautious policy. The usefulness of these methods is illustrated through data envelopment analysis which utilizes an optimizing method of efficiency measurement.