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...

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Vydané v:	Optimization methods & software Ročník 37; číslo 2; s. 753 - 771
Hlavní autori:	Sheen, Heejune, Yamashita, Makoto
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Taylor & Francis 04.03.2022 Taylor & Francis Ltd
Predmet:	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
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