计算机技术与发展2012，Vol.22Issue(8)：30-33,38,5.
带变异算子的非线性惯性权重PSO算法
A Nonlinear Inertia Weight Particle Swarm Optimization Algorithm with Mutation Operator
摘要
Abstract
In order to overcome the shortcomings that standard particle swarm algorithm is easy to fall into local optima and premature convergence, a nonlinear inertia weight particle swarm optimization improved algorithm with mutation operator is proposed. On the basis of the PSO algorithm, firstly the new algorithm introduces nonlinear decreasing strategy to adjust the weight of inertia, balances the particle swarm optimization global and local capabilities. When the optimization is in premature convergence , introduce mutation operator to do random perturbations for the optimal solution of the particle group to improve the ability of the algorithm to jump out of local extreme-Three benchmark functions are tested and the experimental results show that the improved algorithm is able to get rid of local extreme,get the global optimal solution,but also has higher convergence precision and convergence speed than the particle swarm algorithm.关键词
粒子群算法/非线性惯性权重/变异算子Key words
particle swarm optimization/ nonlinear inertia weight/ mutation operator分类
信息技术与安全科学引用本文复制引用
邵洪涛,秦亮曦,何莹..带变异算子的非线性惯性权重PSO算法[J].计算机技术与发展,2012,22(8):30-33,38,5.基金项目
"十一五"国家科技支撑计划课题(2009BAH53B03) （2009BAH53B03）
广西大学硕士研究生科研创新项目(T32602) （T32602）
