Connections between semidefinite relaxations of the max-cut and stable set problems
Mathematical Programming: Series A and B
Solving quadratic (0,1)-problems by semidefinite programs and cutting planes
Mathematical Programming: Series A and B
Approximation algorithms for MAX-3-CUT and other problems via complex semidefinite programming
Journal of Computer and System Sciences - STOC 2001
Conic mixed-integer rounding cuts
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B - Series B - Special Issue: Combinatorial Optimization and Integer Programming
Mathematical Programming: Series A and B
Extending the QCR method to general mixed-integer programs
Mathematical Programming: Series A and B
Hi-index | 0.00 |
We investigate semidefinite relaxations for mixed 0-1 Second-Order Cone Programs. Central to our approach is the reformulation of the problem as a non convex Quadratically Constrained Quadratic Program (QCQP), an approach that situates this problem in the framework of binary quadratically constrained quadratic programming. This allows us to apply the well-known semidefinite relaxation for such problems. This relaxation is strengthened by the addition of constraints of the initial problem expressed in the form of semidefinite constraints. We report encouraging computational results indicating that the semidefinite relaxation improves significantly the continuous relaxation (112% on average) and that it often provides a lower bound very close to the optimal value. In addition, the computational time for obtaining these results remains reasonable.