摘要
针对布谷鸟搜索算法存在收敛速度慢,求解精度低的缺陷,提出一种改进布谷鸟搜索(ICS)算法.将函数动态递减因子引入到步长和发现概率中,并对步长和发现概率进行自适应调整.测试结果表明,改进后的布谷鸟算法在收敛速度和求解精度方面均优于原始布谷鸟算法.
Aimed at cuckoo search algorithm shortcomings of slow convergence and low accuracy, an improved ICS algorithm is proposed. The function dynamic decline factor is introduced into the step length and the discovery probability,which are adjusted adaptively. The test results show that the improved algorithm is superior to the original cuckoo algorithm in both convergence speed and solving accuracy.
作者
罗东
王晓东
段博文
LUO Dong;WANG Xiaodong;DUAN Bowen(School of Science,Xi′an Polytechnic University,Xi′an 710048,China)
出处
《西安工程大学学报》
CAS
2018年第4期479-483,494,共6页
Journal of Xi’an Polytechnic University
基金
陕西省自然科学基金(2016JM1031)
关键词
布谷鸟搜索算法
余弦函数
指数分布
收敛速度
cuckoo search algorithm
cosine function
exponential distribution
convergence speed
