基于对立学习自适应跨代差分进化算法的冷连轧轧制规程多目标优化

Li Yong, Fangfang Lei, Wang Yu
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引用次数: 2

摘要

将对立学习与自适应跨代差分进化算法相结合,提出了一种新的算法。同时,建立了轧制规程的优化模型。选取功率分布、轧制能耗和滑移率作为目标函数。将对立学习自适应跨代差分进化算法应用于优化模型,优化了2.6mm * 900mm规格带钢的轧制计划。结果表明,与采用的轧制规程相比,这三个目标的数值都有所降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Opposition learning adaptive cross-generation differential evolution algorithm based multi-objective optimization of rolling schedule for tandem cold rolling
With the combination of opposition learning and adaptive cross-generation differential evolution algorithm a new algorithm is proposed. Meanwhile the optimization model of rolling schedule is established. Power distribution, rolling energy consumption and the slip rate are selected as objective functions. Applying the opposition learning adaptive cross-generation differential evolution algorithm to the optimization model, rolling schedule for strips with 2.6mm∗900mm specification was optimized. Results show values of the three objectives were reduced compared with the used rolling schedule.
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