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 keeps track of its coordinates

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 toplopy with constrain conditio

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)