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基于模拟退火多种群遗传算法的C-Mn钢生产优化
引用本文:戴元永,陈素琼,申荣法,何宜柱,余亮. 基于模拟退火多种群遗传算法的C-Mn钢生产优化[J]. 宝钢技术, 2003, 0(1): 18-22
作者姓名:戴元永  陈素琼  申荣法  何宜柱  余亮
作者单位:宝钢集团公司,梅山钢铁公司,江苏,南京,210039;安徽工业大学,安徽,马鞍山,243002
摘    要:模拟退火和多种群进化是改进遗传算法的两种主要手段,文章将这两种方法相结合,建立了基于模拟退火的多种群遗传算法,并将该算法应用于C—Mn钢生产时内控成分和轧制工艺的优化,以满足用户对钢产品的力学性能和化学成分的要求。

关 键 词:多种群遗传算法  C-Mn钢  内控成分  轧钢工艺  优化
文章编号:1008-0716(2003)01-0018-05

Optimization of C-Mn Steel Industrial Process Using Multigroup Genetic Algorithm Based on Simulated Annealing
DAI Yuan-yong CHEN Su-qiong SHEN Rong-fa .HE Yi-zhu YU Liang. Optimization of C-Mn Steel Industrial Process Using Multigroup Genetic Algorithm Based on Simulated Annealing[J]. Baosteel Technology, 2003, 0(1): 18-22
Authors:DAI Yuan-yong CHEN Su-qiong SHEN Rong-fa .HE Yi-zhu YU Liang
Affiliation:DAI Yuan-yong CHEN Su-qiong SHEN Rong-fa 2.HE Yi-zhu YU Liang
Abstract:Simulated annealing and multigroup evolution are two helpful methods,which can improve the performance of genetic algorithm.These methods are well combined and a multigroup genetic algorithm based on simulated annealing is derived and applied to the optimization of C-Mn steel industrial process.The satisfied chemical composition and process parameters can be derived according to the required mechanical properties.
Keywords:Multigroup genetic algorithm  C-Mn steel  Internal controlled composition  Rolling technology  Optimization
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