摘要
基于混沌变量遍历性、随机性和规律性的特点,提出一种混沌涡流搜索算法。混沌涡流搜索算法应用混沌映射机制更新涡流搜索算法的备选解,增加了种群多样性,增强了算法的搜索能力,提高了算法的收敛速度。为了验证混沌涡流搜索算法的性能,采用9个著名的测试函数进行测试,并与粒子群算法、人工蜂群算法和萤火虫算法对比,实验结果表明混沌涡流搜索算法具有良好的收敛精度、收敛速度和搜索能力。
The chaos variables own some characteristics, such as ergodicity, random and regularity. Based on these characteristics, a chaotic vortex search algorithm is proposed.The algorithm applies chaotic mapping mechanism to update the candidate solutions of the vortex search algorithm, which can increase its population diversity and enhance its search ability and improve its convergence speed. In order to validate its performance, 9 famous test functions are adopted as the fitness function. Compared with particle swarm optimization algorithm, artificial bee colony algorithm and firefly algorithm, the experiment results show that the chaotic vortex search algorithm possesses preferable convergence rate, convergence speed and search ability.
出处
《燕山大学学报》
CAS
北大核心
2016年第4期329-335,共7页
Journal of Yanshan University
基金
国家自然科学基金资助项目(61573306
61403331)
河北省科技支撑计划资助项目(13211610)
关键词
涡流搜索算法
混沌
映射
优化算法
vortex search algorithm
chaos
mapping
optimization algorithm
