For the green permutation flow-shop scheduling problem(GPFSP) with energy consumption, a hybrid multi-objective evolutionary algorithm based on decomposition(HMOEA/D) is proposed, which aims at optimizing both of the makespan and total energy consumption. Firstly, in order to maintain the diversity of the initial population, a hybrid initialization strategy is used to initialize the population. Then, the tabu search strategy is used as local search operator to make the population jump out of local optima. Finally, an energy-saving strategy is proposed to further optimize the total energy consumption objective. Through the simulation of the standard benchmarks, and compared with the representative algorithm, the experimental results show that the proposed algorithm achieves better performance.