摘要
粒子群优化算法在众多的优化问题上表现出良好的性能,已广泛应用于很多领域,但存在早熟收敛的问题,粒子极易陷入局部最优解.从提高收敛速度等方面对算法改进进行研究,并通过仿真实验证明改进算法的可行性,一定程度上提高了算法的性能.
Particle swarm optimization algorithm has good performance in numerous optimization problem,and has been widely used in many fields.But there are problems of premature convergence,and particle easily goes into the local optimal solution.We improve from convergence,prove the feasibility of the algorithm through the simulation experiment,and to a certain extent,improve the performance of the algorithm more better of.
出处
《太原师范学院学报（自然科学版）》
2011年第2期74-76,115,共4页
Journal of Taiyuan Normal University:Natural Science Edition
关键词
粒子群算法
收敛速度
收缩因子
群智能
PSO
convergence speed
shrinkage factors
swarm intelligence
