A high-dimensional multi-objective multi-directional co-evolutionary algorithm(HMMCA) is proposed. Firstly, the multi-objective optimization problem is decomposed into multiple directions for optimization by using a set of direction vector, and a hybrid mutation strategy is proposed to improve the convergence performance in every direction. Then, an innovative interactive fuzzy dominance and crowding factor are used to maintain the size of external archive. The proposed algorithm is compared to 3 state-of-the-art MOEAs on benchmark test problems. Simulation results show that the HMMCA has obvious advantage in convergence and distribution than other algorithms.