PSO 算法属于进化算法的一种，和模拟退火算法相似，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。粒子群算法是一种并行算法。(The PSO algorithm is a kind of evolutionary algorithm. Similar to the simulated annealing algorithm, it also starts from the random solution and iteratively finds the optimal solution. It also evaluates the quality of the solution through fitness, but it is simpler than the genetic algorithm rules. It does not have the "Crossover" and "Mutation" operations of the genetic algorithm. It seeks the global optimum by following the current searched optimal value. This kind of algorithm has attracted much attention from the academic community because of its advantages of easy implementation, high precision and fast convergence. It also shows its superiority in solving practical problems. Particle swarm algorithm is a parallel algorithm.)