| Article ID: | iaor20032540 |
| Country: | Netherlands |
| Volume: | 116 |
| Issue: | 1 |
| Start Page Number: | 205 |
| End Page Number: | 228 |
| Publication Date: | Jan 2003 |
| Journal: | Journal of Optimization Theory and Applications |
| Authors: | Chen X., Qi L., Wei Z. |
| Keywords: | programming: quadratic |
In this paper, we propose and analyze a sequential quadratic programming-type method for solving linearly constrained convex minimization problems where the objective functions are too complex to be evaluated exactly. Some basic results for global convergence and local superlinear convergence are obtained according to the properties of the approximation sequence. We illustrate the applicability of our approach by proposing a new method for solving two-stage stochastic programs with fixed recourse.