Exploiting aggregate sparsity in second-order cone relaxations for quadratic constrained quadratic programming problems

Among many approaches to increase the computational efficiency of semidefinite programming (SDP) relaxation for nonconvex quadratic constrained quadratic programming problems (QCQPs), exploiting the aggregate sparsity of the data matrices in the SDP by Fukuda et al. [Exploiting sparsity in semidefin...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Optimization methods & software Jg. 37; H. 2; S. 753 - 771
Hauptverfasser:	Sheen, Heejune, Yamashita, Makoto
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Taylor & Francis 04.03.2022 Taylor & Francis Ltd
Schlagworte:	aggregate sparsity chordal sparsity Computational efficiency Computing time Mathematical analysis Matrices (mathematics) Quadratic constrained quadratic programming Quadratic programming second-order cone programming Semidefinite programming Sparsity
ISSN:	1055-6788, 1029-4937
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!