摘要
为解决基本差分进化算法的缺陷,利用布谷鸟搜索(CS)算法寻优能力强的优点,在DE每次完成选择操作后,不直接进入下一次迭代,而是引入CS算法,继续进行搜索,这样就增加了粒子的搜索活力,从而得到一种新的差分进化算法。经过对6个标准测试函数的大量实验计算表明,该算法能有效克服DE算法的缺陷,使寻优精度有较大改进。将算法应用于求解非线性方程组问题,给出了数值算例。
In order to solve the basic differential evolutionary algorithm＇s drawback, taking advantage of Cuckoo Search（CS） algorithm optimization capability, after finishing the selection operation in DE, going to the next iteration is indirect, the CS algorithm is introduced to continue the search, the particle search＇ s activity is improved and a new DE algorithm is got. Massive experiments of six standard benchmark functions suggest that this novel hybrid algorithm effectively overcomes the disadvantages of DE algorithm. It produces a conspicuous effect, which results in satisfactory outcome in experiments. The CS-DE method is applied to solving nonlinear equations and the numerical examples are proposed.
出处
《计算机工程与应用》
CSCD
2013年第9期57-60,共4页
Computer Engineering and Applications
基金
国家自然科学基金(No.70901073)
中央高校基本科研专项基金项目(No.JGK101676)
关键词
差分进化算法
布谷鸟搜索算法
混合算法
非线性方程组
differential evolution algorithm
Cuckoo Search（CS） algorithm
hybrid algorithm
nonlinear equations
