摘要
粒子群算法是一种广受关注的启发式全局最优搜索算法。在分析现有的一些改进算法的基础上,提出了一种利用Arnold混沌映射和单维度扰动项的改进粒子群算法。算法通过改善单个粒子的搜索活力来增强粒子群的全局最优搜索能力。仿真测试表明,该算法能够较好地保持种群的多样性,粒子群优化性能有较大提高。
Particle swarm optimization is one of the heuristic global optimization algorithms, which has attracted vast attentions of researchers. Based on the analysis of the current improved algorithm,one improved algorithm was proposed in this paper, which employs Arnold chaotic map and one dimension disturbance term to improve the particle swarm algorithm. In the proposed algorithm, the researching ability of global optimization of particle swarm is enhanced through the improving of single particle. The simulation results show that the algorithm can keep the population＇s diversity better, and the performance of the particle swarm is increased notably.
出处
《计算机科学》
CSCD
北大核心
2010年第6期268-270,共3页
Computer Science
关键词
粒子群优化
ARNOLD映射
单维度扰动
Particle swarm optimization, Arnold map,One dimension disturbance
