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A MAX-CUT formulation of 0/1 programs. (English) Zbl 1408.90222
Summary: We show that the linear or quadratic 0/1 program \(\mathbf{P} \text{: } \min \{\mathbf{c}^T \mathbf{x} + \mathbf{x}^T \mathbf{F} \mathbf{x} : \mathbf{A} \mathbf{x} = \mathbf{b}; \mathbf{x} \in \{0, 1 \}^n \},\) can be formulated as a MAX-CUT problem whose associated graph is simply related to the matrices \(\mathbf{F}\) and \(\mathbf{A}^T \mathbf{A}\). Hence the whole arsenal of approximation techniques for MAX-CUT can be applied. We also compare the lower bound of the resulting semidefinite (or Shor) relaxation with that of the standard LP-relaxation and the first semidefinite relaxations associated with the Lasserre hierarchy and the copositive formulations of \(\mathbf{P}\).

90C20 Quadratic programming
90C10 Integer programming
90C22 Semidefinite programming
GloptiPoly; Mosek
Full Text: DOI
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