SDP-quality bounds via convex quadratic relaxations for global optimization of mixed-integer quadratic programs
We consider the global optimization of nonconvex mixed-integer quadratic programs with linear equality constraints. In particular, we present a new class of convex quadratic relaxations which are derived via quadratic cuts. To construct these quadratic cuts, we solve a separation problem involving a...
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Veröffentlicht in: | Mathematical programming 2022-11, Vol.196 (1-2), p.203-233 |
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Sprache: | eng |
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