SpeeDP: A new algorithm to compute the SDP relaxations of Max-Cut for very large graphs

We consider low-rank semidefinite programming (LRSDP) relaxations of unconstrained {-1,1} quadratic problems (or, equivalently, of Max-Cut problems) that can be formulated as the nonconvex nonlinear programming problem of minimizing a quadratic function subject to separable quadratic equality constraints. We prove the equivalence of the LRSDP problem with the unconstrained minimization of a new merit function … Read more