Multi-objective Optimization Of Rolling Schedule Based On Improve Immune Clone Algorithm

In the computer control system of cold rolling, the rolling schedule setting is the core content of cold rolling production control parameters. The reasonable rolling schedule can make cold tandem rolling running efficiently, achieve better control effect, and can reduce production energy consumption and improve the quality of products. With the unceasing development of rolling technology and quality requirement enhances unceasingly, rolling schedule set by a single goal has been unable to meet the needs of production, currently rolling schedule optimized by multi-objective algorithm is widely used. Therefore in this paper, according to the actual needs of production, based on improved the immune clone multi-objective algorithm, made a deeply research of multi-objective optimization method of rolling schedule.Firstly, analyzing evolutionary mechanism of the immune clone multi-objective algorithm, in order to accelerate convergence speed mutation strategy of the algorithm is improved. By the differential variation and cloud model method, adaptive individual variation is more targeted, it can increase the search scope of the algorithm, and improve the convergence of the algorithm.Secondly, making an analysis and research of all kinds of multi-objective individuals cutting mechanism, based on evolutionary population and memory population characteristics in immune clone multi-objective algorithm and roles in the optimization process, a mixed cropping selection mechanism is designed. It can select individual of evolutionary population and memory population respectively; prevent individuals in the population are too dense; improve the individual distribution in the algorithm.Finally, based on the problem of coupling and restrict each other between objective functions and selecting weight difficultly, taking a five-stand cold tandem rolling production line in Tangshan as example, constructing target load of the power distribution, excellent flatness and the slip rate, a multi-objective rolling schedule objective function is established and optimized by the improved multi-objective optimization method. Test results show that this algorithm can quickly converge to the Pareto frontier, and obtain the distribution of good solution set; the different preferences of rolling schedule optimized can meet the requirements of different choices. Compared with the original schedule, the usage mode of the rolling mills is more reasonable; the utilization efficiency of the rolling mills is promoted; steel plate shape and surface quality are improved; the probability of scratch is reduced. It plays a guiding role for the secondary setting calculation.