粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(（Evolu2tionary Algorithm - EA）。PSO 算法属于进化算法的一种，和遗传算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。-Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is the recent development of a new evolutionary algorithm ((Evolu2tionary Algorithm- EA). PSO algorithm is an evolutionary algorithm, and similar genetic algorithm, it is also starting from a random solution, find the optimal solution by iteration, it is also used to evaluate the fitness solution through quality, but it is much simpler than the rules of the genetic algorithm, it is not genetic algorithm " cross"　(Crossover) and " alternative"　(Mutation) operations, which follow through to the optimal value of the current search to find the global optimum. This algorithm is known for its easy implementation, high accuracy, fast convergence, etc. attracted academic attention, and in solving practical problems to demonstrate its superiority.