  This paper focuses on the study of a mathematical program with equilibrium
constraints, where the objective and the constraint functions are all
polynomials. We present a method for finding its global minimizers and global
minimum using a hierarchy of semidefinite programming (SDP) relaxations and
prove the convergence result for the method. Numerical experiments are
presented to show the efficiency of the proposed algorithm.
