Rolling schedule design for the ESP rolling process based on NSGA-II-DE.

Abstract

Multiple processes connected closely during the endless strip production (ESP) rolling, it is difficult to obtain the global optimal solution by multi-objective modelling of a single process, and the parameters to be optimized coupled with each other. To obtain the optimal solution, a multi-objective optimization model combining the power consumption, product quality, and loading balance was proposed for the design of an ESP rolling schedule. The thickness and heating temperature were simultaneously taken as the decision variables for coupling the temperature and loading in the rolling process, and the non-dominated sorting genetic algorithm-II (NSGA-II) based on differential evolution (NSGA-II-DE) was applied to obtain the Pareto solutions. To select an optimal solution, a satisfaction function was designed and applied to fully utilize the Pareto solutions. Furthermore, to prove the precision and efficiency of the method, the online schedule and that obtained by the NSGA-II method were compared. The results proved that the final selected solution had better quality and a more balanced loading force than the other two types, which could provide guidance for the actual production process.