中文摘要：

布谷鸟搜索（CS）算法是一种新型的生物启发式算法.为了提高算法对不同优化问题的适应能力,根据反馈控制原理提出一种基于种群特征反馈的布谷鸟搜索（SFFCS）算法,将年龄结构、变异成功率等种群特征作为反馈信息引入算法框架,动态调节算法参数,同时引入双进化策略机制和策略选择概率,加强算法对局部搜索和全局搜索的平衡能力.对标准测试函数和电力系统最优潮流问题进行数值实验,实验结果表明,SFFCS算法具有较好的收敛性能和适应能力,验证了所提出算法的有效性和工程应用价值.

英文摘要：

Cuckoo search（CS） is a novel nature-inspired algorithm. For the sake of adaptation to various optimization problems, an improved CS algorithm is proposed, named swarm feature feedback cuckoo search（SFFCS） algorithm, on the basis of the feedback control principle. Swarm features such as age structure and success rate of mutation are introduced as feedback information for adjusting the parameters dynamically. Double evolutionary strategies and strategy selection probability are also introduced to balance the capability between local and global search. Numerical experiments on benchmark functions and the optimal power flow problem of the electrical system are conducted. The results indicate that the SFFCS algorithm behaves strong performance on convergence and adaptation, and show the effectiveness and practical engineering value of the proposed algorithm.