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1. A modified particle swarm optimization algorithm based on dynamic learning factors and sharing method(基于动态因子和共享适应度的改进粒子群算法)

Author

TANYifeng(谭熠峰), SUNTingting(孙婷婷), and XUXinming(徐新民)

Subjects
动态, 学习因子, 共享适应度, 粒子群算法, Electronic computers. Computer science, QA75.5-76.95, Physics, QC1-999
Abstract

为提高粒子群算法的收敛速度和优化性能，避免陷入局部最优，提出了一种基于动态学习因子和共享适应度函数的改进粒子群算法.在惯性权重w随着迭代次数非线性减少而动态调整学习因子的基础上，引入共享适应度函数.当算法未达到终止条件而收敛时，利用粒子和最优解间距离挑选一批粒子重新初始化形成新群体，并用共享适应度函数对新群体进行评价，新旧2个群体分别追随自己的局部最优解直至迭代结束.对4个典型多峰复杂函数的测试结果表明，该改进算法不仅加快了寻得最优解的速度，而且提高了粒子群算法全局收敛的性能.

Published
2016
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