Description
Efficiently and robustly solving the Karush-Kuhn-Tucker
(KKT) systems arising in optimization methods to solve large scale nonlinear programming problems is a big
challenge that requires a good insight into both the linear algebra and optimization fields. Our aim is to
contribute to the development of appropriate preconditioners for iterative methods designed to solve such
saddle-point systems arising in constrained optimization, exploiting their special structure and properties.
(KKT) systems arising in optimization methods to solve large scale nonlinear programming problems is a big
challenge that requires a good insight into both the linear algebra and optimization fields. Our aim is to
contribute to the development of appropriate preconditioners for iterative methods designed to solve such
saddle-point systems arising in constrained optimization, exploiting their special structure and properties.
| Status | Active |
|---|---|
| Effective start/end date | 3/10/11 → … |