粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，1995 年由Eberhart 博士和kennedy 博士提出，源于对鸟群捕食的行为研究 。该算法最初是受到飞鸟集群活动的规律性启发，进而利用群体智能建立的一个简化模型。粒子群算法在对动物集群活动行为观察基础上，利用群体中的个体对信息的共享使整个群体的运动在问题求解空间中产生从无序到有序的演化过程，从而获得最优解。(Particle swarm optimization (PSO) is an evolutionary computation technology (Evolutionary Computation). It was put forward by Dr. Eberhart and Kennedy in 1995, and it originated from the behavior of bird predation. The algorithm was initially inspired by the regularity of the activities of the birds cluster, and then used a simplified model established by the swarm intelligence. Based on the observation of animal cluster action behavior, particle swarm algorithm (PSO) makes use of individuals' information sharing in the group to make the whole group's motion in problem solving space evolve from disorder to order, so as to get the optimal solution.)