Particle swarm optimization (PSO) is a population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling. Each particle k

这个是基于环形拓扑结构的约束微粒群算法，对原来的算法做了改进，只用到了一个邻居节点，效果与基本的微粒群算法大致相当。但是在对多模函数的计算上，优于基本的微粒群算法。这个算法的运行平台是GPUmat,需要的运行环境有：Matlab, GPU, GPUmat, Visual Studio.-This the modified particle swarm optimization algorithm that based on ring t

粒子群优化研究工具箱是为了协助解决粒子群优化（PSO）过早收敛问题的论文研究。(Gbest PSO, Lbest PSO, RegPSO, GCPSO, MPSO, OPSO, Cauchy mutation, and hybrid combinations)