计量学报2017，Vol.38Issue(4)：453-458,6.DOI:10.3969/j.issn.1000-1158.2017.04.15
基于反向学习的差分进化算法的冷轧负荷分配
A Differential Evolution Algorithm Based on Opposite Learning in Load Distribution for Cold Rolling
摘要
Abstract
A differential evolution algorithm based on opposite learning is presented.In the proposed algorithm, to increase the diversity of initial population, the opposite learning is employed.In addition, the mutation strategy assigned to each individual is adaptively selected according to the selected probability, and the control parameters are generated by evolution-based monotone decreasing function and Logistic mapping.A large amount of simulation experiments have been made.Experimental results show that the proposed algorithm is better than other differential evolution algorithms.At last, the proposed algorithm is applied in load distribution for tandem cold rolling.关键词
计量学/差分进化/自适应/反向学习/负荷分配/冷连轧Key words
metrology/differential evolution/self-adaptive/opposite learning/load distribution/tandem cold rolling分类
通用工业技术引用本文复制引用
赵志伟..基于反向学习的差分进化算法的冷轧负荷分配[J].计量学报,2017,38(4):453-458,6.基金项目
河北省高等学校科学技术研究青年基金项目(QN2017416) （QN2017416）
河北省科技计划项目(16212302) （16212302）
唐山学院博士创新基金 （）
