一种带逆反的粒子群算法  

Particle Swarm Optimization Algorithm with Reverse Thinking Particles

作　　者：张晓明[1] 王儒敬[1] 

机构地区：[1]中国科学院合肥智能机械研究所,合肥230031

出　　处：《计算机科学》2006年第10期156-159,共4页Computer Science

基　　金：国家自然科学基金重点项目(69835010)

摘　　要：粒子群算法(PSO)是一种典型的基于群体智能的优化算法,但其在速度较小时,容易陷入局部最优解;本文提出一种带逆反的粒子群算法(PSORTP),并对其全局收敛性进行了理论分析,证明该算法能够以概率1收敛于全局最优解,最后以典型的函数优化问题的仿真实验及与经典方法的PSO的对比,验证了PSORTP的有效性。The particle swarm optimization algorithm is a kind of intelligent optimization algorithm. This algorithm is prone to be fettered by the local optimization solution when the particle＇s velocity is small. This paper presents a novel particle swarm optimization algorithm named particle swarm optimization with reverse thinking particles which is guaranteed to converge to the global optimization solution with probability one. And we also make the global convergence analysis. Finally, two function optimizations are simulated to show that the PSORTP is better and more efficient than the PSO with inertia weights.

关 键 词：群集智能 粒子群算法 逆向思维粒子 全局最优性 

分 类 号：O211.5[理学—概率论与数理统计]