A branch-and-cut algorithm using polar cuts for solving nonconvex quadratic programming problems

In this paper, we propose a branch-and-cut algorithm for solving a nonconvex quadratically constrained quadratic programming (QCQP) problem with a nonempty bounded feasible domain. The problem is first transformed into a linear conic programming problem, and then approximated by semidefinite program...

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Vydáno v:	Optimization Ročník 67; číslo 2; s. 359 - 375
Hlavní autoři:	Deng, Zhibin, Fang, Shu-Cherng, Lu, Cheng, Guo, Xiaoling
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Philadelphia Taylor & Francis 01.02.2018 Taylor & Francis LLC
Témata:	Algorithms Branch & bound algorithms Branch-and-cut algorithm Feasibility Lower bounds nonconvex quadratically constrained quadratic programming Optimization polar cut Quadratic programming Semidefinite programming semidefinite relaxation
ISSN:	0233-1934, 1029-4945
On-line přístup:	Získat plný text
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