【摘要】 该文以负荷均衡分配、最优板形等可变函数为目标，提出了一种基于改进文化基因算法(MA)的铝1+4热连轧轧制规程优化方法。算法外部框架采用改进的自适应遗传算法(AGA)进行全局搜索和种群局部搜索，以简化序列二次规划(RSQP)算法进行二次局部搜索，实现连轧规程优化。在非线性目标函数和多目标约束条件下，对热连轧的负荷分配及最优板形进行了规程优化。经某厂生产验证：优化后的方案可实现连轧的负荷均衡分配，且产品质量较经验算法提升了约10.8%。更多还原

【Abstract】 Aiming at the variable functions such as load balanced distribution and optimal shape, a rolling schedule optimization method for aluminum 1+4 hot strip rolling based on improved memetic algorithm(MA)is proposed here. The external framework of the algorithm adopts the improved adaptive genetic algorithm(AGA)for global search and population local search, using the reduced successive quadratic programming(RSQP)for secondary local search to optimize the continuous rolling schedule. Under the conditions of nonlinear objective function and multi-objective constraints, the schedule optimization of load distribution and optimal shape of hot strip rolling is carried out. The production verification of a factory shows that the optimized scheme can realize the balanced load distribution of strip rolling, and the product quality is improved by about 10.8% compared with the empirical algorithm.更多还原