计算机工程与应用2011，Vol.47Issue(17)：42-44,55,4.DOI:10.3778/j.issn.1002-8331.2011.17.012
带变异算子的自适应粒子群优化算法
Adaptive particle swarm optimization algorithm with hybrid mutation operator.
摘要
Abstract
A modified Particle Swarm Optimization (PSO) is proposed to improve the performance of standard PSO that is easily trapped in local optimum and has a slow convergence rate in the late period. On the basis of standard PSO,the modified algorithm applies some methods such as citing a nonlinearly descending inertia, changing the velocity iteration formula and introducing the mutation operator during the running time. The experimental results show that the new algorithm has great advantage of convergence property over standard PSO.关键词
粒子群优化算法/变异算子/自适应惯性权重/全局优化Key words
Particle Swarm Optimization(PSO)/mutation operator/adaptive inertia weight/global optimization分类
信息技术与安全科学引用本文复制引用
赵志刚,常成..带变异算子的自适应粒子群优化算法[J].计算机工程与应用,2011,47(17):42-44,55,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60973074) （the National Natural Science Foundation of China under Grant No.60973074）
广西教育厅科研项目(No.桂教科研200626). （No.桂教科研200626）
