A Differential Evolution Algorithm Based on Opposite Learning in Load Distribution for Cold Rolling
ZHAO Zhi-wei1,2
1.Department of Computer Science and Technology, Tangshan College, Tangshan, Hebei 063000, China
2. Department of Automation, School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
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.
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.
ZHAO Zhi-wei. A Differential Evolution Algorithm Based on Opposite Learning in Load Distribution for Cold Rolling. Acta Metrologica Sinica, 2017, 38(4): 453-458.
2017, Vol. 38 
