Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear) ...

To overcome this weakness, we propose to keep the binary constraints intact and apply the semidefinite relaxation (SDR) technique to continuous variables. Although the resulting relaxation takes the ...

Finding a solution when the problem is of large size to be of practical interest typically requires relaxation. Semidefinite relaxation usually yields tight bounds, but its computational complexity is ...

A real matrix is positive semidefinite if it can be decomposed as A=BB′. In some applications the matrix B has to be elementwise nonnegative. If such a matrix exists, A is called completely positive.

It introduces convex relaxation into VP estimation by formulating the problem as a quadratically constrained quadratic program (QCQP) and relaxing it into a convex semidefinite program (SDP). This ...