计算机技术与发展Issue(10)：38-43,6.DOI:10.3969/j.issn.1673-629X.2015.10.008
基于变尺度法和自适应步长的布谷鸟搜索算法
A Cuckoo Search Algorithm Based on Variable Metric Method and Adaptive Step
摘要
Abstract
Cuckoo Search ( CS) is a novel meta-heuristic algorithm. Aiming at the defects of weak local search ability,slow convergence velocity and low convergence accuracy,a modified CS algorithm based on DFP and adaptive step is proposed in this paper. In the im-proved cuckoo search algorithm,the step of Lévy flight nonlinear dynamic changes improve convergence velocity. After evolved from Lévy flights and elimination mechanism,the cuckoo populations rapidly access to global minima by DFP. Sixth representative benchmark functions are used to test the performance of DACS algorithm and CS algorithm respectively. The conclusions indicate that DACS algo-rithm has faster convergence speed,higher convergence accuracy and robustness,compared with CS algorithm. Meanwhile,DACS algo-rithm keeps strong global search capability,which is particularly suitable for the optimization of multimodal function and high dimension function.关键词
布谷鸟搜索/变尺度法/自适应步长/全局寻优Key words
cuckoo search/variable metric method/adaptive step/global optimization分类
信息技术与安全科学引用本文复制引用
江浩,阮奇..基于变尺度法和自适应步长的布谷鸟搜索算法[J].计算机技术与发展,2015,(10):38-43,6.基金项目
国家基础科学人才培养基金资助项目(J1103303) （J1103303）
