免疫遗传算法对精轧机组负荷分配的优化

Immune Genetic Algorithms(IGA)Based Scheduling Optimization for Finisher

提出基于ＩＧＡ模型的热连轧精轧机组负荷分配的智能优化新方法，该方法具有计算 精度高、速度快等特点，且适合在线计算．实验数据对比分析结果表明了该方法的有效性，为热 连轧精轧机组轧制规程的智能优化设计提供了一条新途径．

A new way was presented to optimize the scheduling of finisher of hot continuous rolling mills by means of Immune Genetic Algorithm. The method has advantages such as fast searching speed, high com-puting precision, suiting to on-line calculation. Test results show that the new method is valid. This method also provides another way for optimal design of the schedule of finisher of hot continuous mills.