  This is Part II of a study on mixed-integer programming (MIP) relaxation
techniques for the solution of non-convex mixed-integer quadratically
constrained quadratic programs (MIQCQPs). We set the focus on MIP relaxation
methods for non-convex continuous variable products and extend the well-known
MIP relaxation normalized multi-parametric disaggregation technique (NMDT),
applying a sophisticated discretization to both variables. We refer to this
approach as doubly discretized normalized multiparametric disaggregation
technique (D-NMDT). In a comprehensive theoretical analysis, we underline the
theoretical advantages of the enhanced method D-NMDT compared to NMDT.
Furthermore, we perform a broad computational study to demonstrate its
effectiveness in terms of producing tight dual bounds for MIQCQPs. Finally, we
compare D-NMDT to the separable MIP relaxations from Part I and a
state-of-the-art MIQCQP solver.
