中文摘要：

A multi-objective optimization model for draft scheduling of hot strip mill was presented,which considers rolling power minimizing,rolling force ratio distribution and good strip shape as the objective functions.A multi-objective differential evolution algorithm based on decomposition (MODE/D) was used to solve this model.The two-objective and three-objective optimization experiments were performed respectively to demonstrate the optimal solutions of trade-off.The simulation results show that MODE/D can obtain a good Pareto-optimal front,which suggests a series of alternative solutions to draft scheduling.The extreme Pareto solutions are found feasible and the centres of the Pareto fronts give a good compromise.The conflict exists between each two ones of three objectives.The final optimal solution is selected from the Pareto-optimal front by the importance of objectives,and it can achieve a better performance in all objective dimensions than the empirical solutions.Finally,the practical application cases confirm the feasibility of the multi-objective approach,and the optimal solutions can gain a better rolling stability than the empirical solutions,and strip flatness decreases from (0±163) IU to (0±45) IU in industrial production.

英文摘要：

A multi-objective optimization model for draft scheduling of hot strip mill was presented, rolling power minimizing, rolling force ratio distribution and good strip shape as the objective functions. A multi-objective differential evolution algorithm based on decomposition （MODE/D）. The two-objective and three-objective optimization experiments were performed respectively to demonstrate the optimal solutions of trade-off. The simulation results show that MODE/D can obtain a good Pareto-optimal front, which suggests a series of alternative solutions to draft scheduling. The extreme Pareto solutions are found feasible and the centres of the Pareto fronts give a good compromise. The conflict exists between each two ones of three objectives. The final optimal solution is selected from the Pareto-optimal front by the importance of objectives, and it can achieve a better performance in all objective dimensions than the empirical solutions. Finally, the practical application cases confirm the feasibility of the multi-objective approach, and the optimal solutions can gain a better rolling stability than the empirical solutions, and strip flatness decreases from （0± 63） IU to （0±45） IU in industrial production.