Abstract: Aiming at green sustainable development, a multi-objective hybrid flow shop scheduling model is established, with minimizing the maximum makespan, carbon emission and noise, by quantifying green index evaluation method. To solve the model, a hybrid discrete multi-objective imperial competition algorithm (HDMICA) is proposed. The population initialization method based on chaotic reverse learning strategy is adopted to improve the diversity of the initial population. Based on the model in this research, three effective local search strategies are designed to improve the local search capability of the algorithm. The feasibility and effectiveness of the proposed algorithm are verified by experiments.