介绍一种新的生物启发算法一布谷鸟搜索(CS)及其相关的Levy飞行搜索机制.为了进一步提高算法的适应性,将反馈引入算法框架,建立了CS算法参数的闭环控制系统.将Rechenberg的1/5法则作为进化的评价指标,引入学习因子平衡种群的多样性和集中性,提出动态适应布谷鸟算法(DACS).最后,通过数值实验验证了所提出算法的有效性.
A novel bio-inspired algorithm, cuckoo search(CS), is introduced along with the related L6vy fight mechanism. In order to improve the adaptation of this algorithm, a feedback control scheme of algorithm parameters is adopted in CS. By utilizing Rechenberg's 1/5 criteria to evaluate evolution process, and introducing the learning factor, the diversification and intensification of population are well balanced. The dynamic adaptation cuckoo search(DACS) algorithm is proposed. Finally, numerical experiment results show the effectiveness of the proposed algorithm.