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轧制规程设定是铝热连轧轧制过程控制的重要内容,轧制规程的好坏直接影响产品质量和生产效率。针对铝热连轧过程轧制规程优化目标的多样性问题,提出改进的混沌多目标量子遗传算法对轧制规程进行优化。该算法初始化引入混沌序列并采用量子位概率指导的实数交叉与混沌变异相结合的方法,同时采用非支配排序、自适应网格及外部解集等多目标优化策略,从而提高了寻优效率和收敛速度。以等相对负荷、末机架板形良好为目标函数,对河南某铝厂热连轧机进行轧制规程优化。仿真结果表明,优化规程的打滑因子和负荷系数优于原始规程。
Rolling schedule setting is an important part of aluminum hot rolling process control, the quality of rolling schedule directly affect the product quality and production efficiency. Aiming at the variety of rolling schedule optimization targets in the hot strip mill, an improved chaotic multi-objective quantum genetic algorithm is proposed to optimize the rolling schedule. The algorithm initializes the method of combining real number chaos and chaotic mutation, which is introduced chaotic sequence and guided by quantum bit probability. At the same time, the multi-objective optimization strategy such as non-dominated scheduling, adaptive grid and external solution set is used to improve the optimization efficiency and convergence speed. Taking the relative load and the good shape of the end frame plate as the objective function, the rolling schedule of a hot strip mill in Henan was optimized. The simulation results show that the slippage factor and load factor of the optimization procedure are better than the original procedure.