Abstract
We investigate the use of linear programming tools for solving semidefinite programming relaxations of quadratically constrained quadratic problems. Classes of valid linear inequalities are presented, including sparse PSD cuts, and principal minors PSD cuts. Computational results based on instances from the literature are presented.
AMS(MOS) subject classifications. 90C57.
Supported by NSF grant NSF-0750826.
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Qualizza, A., Belotti, P., Margot, F. (2012). Linear Programming Relaxations of Quadratically Constrained Quadratic Programs. In: Lee, J., Leyffer, S. (eds) Mixed Integer Nonlinear Programming. The IMA Volumes in Mathematics and its Applications, vol 154. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1927-3_14
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DOI: https://doi.org/10.1007/978-1-4614-1927-3_14
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