精英反向学习的单纯形交叉布谷鸟搜索算法

Elite Opposition-based Learning Based Simplex Crossover Cuckoo Search Algorithm

提出一种加强搜索能力的改进布谷鸟搜索算法,该算法采用精英反向学习策略促使Lévy Flights随机走动中的部分精英个体进行反向搜索,以避免搜索新个体的趋同性;并采用单纯形交叉操作在Biased随机走动中随机选择一个个体进行精细搜索,以降低搜索的盲目性以及低效性.另外,提出的算法采用混沌映射模型实现发现概率参数的自适应控制.仿真实验结果表明,该算法能够总体上有效改善算法的搜索能力和收敛速度.

Cuckoo search algorithm iteratively uses L ＆#233;vy Flights random walk and Biased random walk to search for new individuals.In this paper,an enhanced cuckoo search was proposed,which employed elite op-position-based learning,simplex crossover and parameter control for the fraction probablity.The elite opposi-tion-based learning strategy was used to avoid the new individuals being homogeneous in the L ＆#233;vy Flights ran-dom walk.The simplex crossover strategy was utilized to reduce the inefficience of Biased random walk.The chaotic map was used to adaptively adjust the parameter pa to balance the exploration and the exploitation. The results of experiment showed the proposed strategies were overall effective,and make a great improvement on the performance of solution and convergence.