计算机工程与应用Issue(9)：111-115,5.DOI:10.3778/j.issn.1002-8331.1206-0460
基于自适应扰动的粒子群优化算法
Particle Swarm Optimization based on adaptive disturbance
摘要
Abstract
In order to avoid premature convergence of Particle Swarm Optimization(PSO), a new PSO algorithm based on Adaptive Disturbance(ADPSO)is proposed to help trapped particles escape from local minima. Experiments are con-ducted on nine multimodal functions, including four rotated functions, to verify the effectiveness of ADPSO. Simulation results demonstrate that this approach outperforms five other PSO algorithms.关键词
粒子群优化算法/自适应扰动/多峰函数/全局优化Key words
Particle Swarm Optimization(PSO)/adaptive disturbance/multimodal function/global optimization分类
信息技术与安全科学引用本文复制引用
王敏,唐俊..基于自适应扰动的粒子群优化算法[J].计算机工程与应用,2014,(9):111-115,5.基金项目
湖南省教育厅资助科研项目（No.10C0082，No.11C0231，No.11C0232，No.11C0477）。 （）
