摘要
为了解决粒子群优化算法容易陷入局部最优和后期搜索精度不高的问题,提出了带有合作算子的改进粒子群算法。合作算子和粒子运动公式的动态调整改善种群的多样性并且提高了搜索精度。从算法的收敛性、准确性和稳定性等方面对这种改进算法进行分析和实验,发现均优于标准粒子群优化(PSO)算法。
To avoid the problem of premature convergence and poor accuracy in later period, an improved particle swarm optimization （IPSO） algorithm with cooperation operator is introduced. Cooperation operator and dynamic adjustment of particle movement formula improve the diversity of the population and algorithm accuracy. Its convergence, accuracy, and stability with two benchmark function are test. It is found that IPSO outperforms the normal PSO algorithm clearly.
出处
《电脑与电信》
2012年第6期34-35,共2页
Computer & Telecommunication
关键词
粒子群算法
合作算子
群智能
particle swarm optimization algorithm
cooperation operator
swarm intelligence
