Rank of Handelman hierarchy for Max-Cut

We consider a hierarchical relaxation, called Handelman hierarchy, for a class of polynomial optimization problems. We prove that the rank of Handelman hierarchy, if applied to a standard quadratic formulation of Max-Cut, is exactly the same as the number of nodes of the underlying graph. Also we give an error bound for Handelman hierarchy, in terms of its level, applied to the Max-Cut formulation.

► We apply Handelman hierarchy to a standard quadratic formulation of Max-Cut.
► We prove that its rank is equal to the number of nodes and give an error bound.
► Duality between the Handelman hierarchy and RLT is presented.