Abstract
In this paper, we propose and analyze an SQP-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.
| Original language | English |
|---|---|
| Pages (from-to) | 205-228 |
| Number of pages | 24 |
| Journal | Journal of Optimization Theory and Applications |
| Volume | 116 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2003 |
Keywords
- epiconvergence
- global convergence
- SQP method
- stochastic programming
- superlinear convergence
ASJC Scopus subject areas
- Control and Optimization
- Management Science and Operations Research
- Applied Mathematics