基于Tent映射的混沌粒子群优化算法

A Chaotic Particle Swarm Optimization Algorithm Based on Tent Mapping

针对粒子群算法在迭代后期易陷入局部最优的不足,采用Tent映射所产生的混沌序列在粒子个体最优点和全局最优点附近进行混沌搜索,利用混沌搜索的全局遍历性和随机性提高了粒子群优化算法的全局搜索能力和抗早熟收敛性能。几个典型测试函数的仿真结果证明了该算法的可行性。

To enhance the searching efficiency of particle swarm optimization algorithm（PSO）,tent mapping was introduced into PSO as a strategy of chaotic optimization searching to avoid PSO getting into local best and appearing premature convergence.The feasibility of the new algorithm named chaotic particle swarm optimization algorithm based on tent mapping（CTPSO） was verified by some typical test functions given in the paper.The results show that global ergodic property and randomness of chaotic searching can improve the global search capability of PSO effectively.