A maximum partition of a directed weighted graph is partitioning the nodes into two sets such that it maximizes the total weights of edges between the two sets. In this study a genetic algorithm is proposed to solve the maximum partition problem. Experiments performed on randomly generated graphs of different sizes show that the proposed algorithm converges to an optimal solution faster than the existing heuristic algorithm.