| Article ID: | iaor19952295 |
| Country: | Switzerland |
| Volume: | 56 |
| Issue: | 1 |
| Start Page Number: | 189 |
| End Page Number: | 208 |
| Publication Date: | Jun 1995 |
| Journal: | Annals of Operations Research |
| Authors: | Wets Roger J.-B., King Alan J., Kaniovski Yuri M. |
Several exponential bounds are derived by means of the theory of large deviations for the convergence of approximate solutions of stochastic optimization problems. The basic results show that the solutions obtained by replacing the original distribution by an empirical distribution provides an effective tool for solving stochastic programming problems.