An Interior-Point Method for Semidefinite Programming

An Interior-Point Method for Semidefinite Programming

We propose a new interior-point-based method to minimize a linear function of a matrix variable subject to linear equality and inequality constraints over the set of positive semidefinite matrices. We show that the approach is very efficient for graph bisection problems such as max-cut. Other applic...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:SIAM journal on optimization 1996-05, Vol.6 (2), p.342-361
Hauptverfasser: Helmberg, Christoph, Rendl, Franz, Vanderbei, Robert J., Wolkowicz, Henry
Format: Artikel
Sprache:eng
Schlagworte:
Eigenvalues
Inequality
Linear programming
Optimization
Semidefinite programming
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We propose a new interior-point-based method to minimize a linear function of a matrix variable subject to linear equality and inequality constraints over the set of positive semidefinite matrices. We show that the approach is very efficient for graph bisection problems such as max-cut. Other applications include max-min eigenvalue problems and relaxations for the stable set problem.
ISSN:1052-6234
1095-7189
DOI:10.1137/0806020