Abstract
We consider the following quasiconvex optimization problem: minimize the largest eigenvalue of a symmetric definite matrix pencil depending on parameters. A new form of optimality conditions is given, emphasizing a complementarity condition on primal and dual matrices. Newton's method is then applied to these conditions to give a new quadratically convergent interior-point method which works well in practice. The algorithm is closely related to primal-dual interior-point methods for semidefinite programming.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the American Control Conference |
| Publisher | American Automatic Control Council |
| Pages | 836-839 |
| Number of pages | 4 |
| Volume | 1 |
| State | Published - 1994 |
| Event | Proceedings of the 1994 American Control Conference. Part 1 (of 3) - Baltimore, MD, USA Duration: Jun 29 1994 → Jul 1 1994 |
Other
| Other | Proceedings of the 1994 American Control Conference. Part 1 (of 3) |
|---|---|
| City | Baltimore, MD, USA |
| Period | 6/29/94 → 7/1/94 |
ASJC Scopus subject areas
- Control and Systems Engineering