Semidefinite relaxations for quadratically constrained quadratic programming: A review and comparisons

At the intersection of nonlinear and combinatorial optimization, quadratic programming has attracted significant interest over the past several decades. A variety of relaxations for quadratically constrained quadratic programming (QCQP) can be formulated as semidefinite programs (SDPs). The primary...

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Bibliographic Details
Published in:	Mathematical programming Vol. 129; no. 1; pp. 129 - 157
Main Authors:	Bao, Xiaowei, Sahinidis, Nikolaos V., Tawarmalani, Mohit
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer-Verlag 01.09.2011 Springer Nature B.V
Subjects:	Calculus of Variations and Optimal Control; Optimization Combinatorial analysis Combinatorics Computation Constraints Full Length Paper Gaps Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Nonlinearity Numerical Analysis Optimization Production planning Quadratic programming Semidefinite programming Studies Theoretical Semidefinite programming Nonconvex optimization 65K05 90C30 Lagrangian relaxation 90C22 49M29 90C26 Quadratic programming
ISSN:	0025-5610, 1436-4646
Online Access:	Get full text
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