Particle swarm optimization algorithm, also known as particle swarm optimization algorithm (Swarm Optimization Particle), abbreviated as PSO, is a parallel algorithm on the basis of the observation of the behavior of animal clusters, the use of groups of individuals in the information sharing to make the whole group of movement in the problem solving space generated the disorder to the orderly evolution process, thereby obtaining the optimal solution. Particle swarm optimization algorithm and simulated annealing algorithm, it is also the random solution, through the iterative search for the optimal solution, it is through the fitness to uate the quality of the solution, but it is more simple than the genetic algorithm rules, it does not have the genetic algorithm crossover (Crossover) and Mutation operation, it follows the current search to the optimal value to find the global optimal.-Particle swarm optimization algorithm, also known as particle swarm optimization algorithm (Swarm Optimization Particle), abbreviated as PSO, is a parallel algorithm　on the basis of the observation of the behavior of animal clusters, the use of groups of individuals in the information sharing to make the whole group of movement in the problem solving space generated　the disorder to the orderly evolution process, thereby obtaining the optimal solution. Particle swarm optimization algorithm and simulated annealing algorithm, it is also　the random solution, through the iterative search for the optimal solution, it is through the fitness to　uate the quality of the solution, but it is more simple than the genetic algorithm rules, it does not have the genetic algorithm　crossover　(Crossover) and　Mutation　operation, it follows the current search to the optimal value to find the global optimal.