This study addresses the problem of finding an anti-Berge equilibrium in a bimatrix game based on a global search algorithm. Finding the anti-Berge equilibrium reduces equivalently to a quadratic programming with an indefinite matrix and linear constraints, which belongs to a class of global optimization. To solve the problem numerically, we develop a modified parallel tangent algorithm. The proposed algorithm uses the one-dimensional nonlocal search procedure based on the Strongin and parabolas methods. The stop criterion of the algorithm is the sufficient condition for anti-Berge equilibrium. The proposed algorithm is implemented and numerically tested on a range of bimatrix games.