Optimizing eigenvalues of symmetric definite pencils

Jean Pierre A Haeberly, Michael L. Overton

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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 languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
PublisherAmerican Automatic Control Council
Number of pages4
StatePublished - 1994
EventProceedings of the 1994 American Control Conference. Part 1 (of 3) - Baltimore, MD, USA
Duration: Jun 29 1994Jul 1 1994


OtherProceedings of the 1994 American Control Conference. Part 1 (of 3)
CityBaltimore, MD, USA

ASJC Scopus subject areas

  • Control and Systems Engineering


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