Convex relaxations of non-convex mixed integer quadratically constrained programs: projected formulations

A common way to produce a convex relaxation of a Mixed Integer Quadratically Constrained Program (MIQCP) is to lift the problem into a higher-dimensional space by introducing variables Y ij to represent each of the products x i x j of variables appearing in a quadratic form. One advantage of such ex...

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Veröffentlicht in:	Mathematical programming Jg. 130; H. 2; S. 359 - 413
Hauptverfasser:	Saxena, Anureet, Bonami, Pierre, Lee, Jon
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer-Verlag 01.12.2011 Springer Springer Nature B.V
Schlagworte:	Algorithms Applied sciences Calculus of Variations and Optimal Control; Optimization Combinatorics Computation Constraints Construction Exact sciences and technology Full Length Paper Heuristic Linear programming Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Mixed integer Numerical Analysis Operational research and scientific management Operational research. Management science Optimization Quadratic forms Studies Theoretical Variables global optimization 90C26 Nonconvex programming Non convex programming Subgradient optimization Constraint satisfaction Global optimum Linear programming Mixed integer programming Semi definite programming Quadratic programming Cut generation Integer programming Time average Disjunctive programming Heuristic method Relaxation method Non convex analysis
ISSN:	0025-5610, 1436-4646
Online-Zugang:	Volltext
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