摘要
粒子群算法是一种新型的进化计算方法,已在许多领域得到了广泛的应用,但基本粒子群算法在计算过程中易出现过早收敛现象.为此提出了一种改进的粒子群算法,利用差异演化的思想,当陷入局部极小点时,通过一定的策略迫使粒子群摆脱局部极小点.对经典函数的测试计算,验证了方法的正确性和有效性.
Particle swarm optimization(PSO) is a new evolutionary computation method,which has been successfully applied to many fields.But the standard particle swarm optimization is used resulting in premature convergence.An improved particle swarm optimization is presented.Using differential evolution strategy,it can make the solution jump out of the local minimum point.The experimental results of classic functions show that the improved PSO is efficient and feasible.
出处
《郑州大学学报（理学版）》
CAS
2007年第3期109-112,共4页
Journal of Zhengzhou University:Natural Science Edition
基金
河北省科技厅科技攻关项目
编号052135149
关键词
粒子群
差异演化
优化
particle swarm
differential evolution
optimization
