南京大学学报(自然科学版) ›› 2013, Vol. 49 ›› Issue (2): 202209.
孙成富**,张亚红,陈剑洪,陈礼青
Sun Cheng-Fu,Zhang Yu -Hong,Chen Jiun- Honk,Chen Li-Qing
摘要: 在差分进化算法的优化过程中,不断生成更优的解并采用达尔文的“适者生存”思想进行择优
保留,这样的遗弃会导致个体有效成分缺失,并失去对新空间的探索开发能力,降低种群多样性,进而使
算法早熟收敛并陷入局部最优,因此需要改进差分进化算法并权衡算法的空间探索和开发能力,提高解
的精确度和算法收敛速度.为此,基于高斯扰动和免疫搜索策略的差分进化算法被提出.首先,通过生物
免疫系统的信息处理机制实现自适应地修正差分进化算法中的缩放因子和交叉因子,以满足优化过程
中对这两个参数的取值要求;然后,通过基于高斯扰动的交叉操作算子增加种群的多样性,扩展算法的
探索空间,以避免陷入局部最优,进而提高算法的性能.实验结果表明,该优化算法具有良好的寻优
性能.
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