Sorted Weighted Centroid Of PSO Algorithm And Its Application In Tax Planning For Enterprise Employees

PSO is an optimization algorithm.It simulates the action of the bird、fish swram action and to get the optimization through the cooperation in the swarm.The algorithm obtains the evolution of all swarm from changing information between the individuals.The particle can adjust the moving track of themselves from the best location itself ever went previously,the whole swarm ever went previously and the inertia term.Due to the speed of update ability is insufficient,particles in some area closely together and can’t be more wide search,which makes the algorithm premature convergence in the iterative process,the problem of low precision of convergence.In this algorithm,particles are short of variety,little difference between each particle and less information change the swarm to develop,especially in high-dimensional modal optimization problem.Based on analysis the shortage of the PSO,it gives one improved strategy.In the course of evolution,only the optimal particle position of the population is insufficient,and the evolution trend of the whole particle population is also considered.,using the swarm information to guide the evolution.So,another“population centroid” is calculated,the appropriate “population centroid” information can make the next evolution direction be more conducive to the evolution.Based on the these analysis,this paper verifies the effectiveness of the improved strategy through a series of optimization examples,and applies it to the enterprise individual income tax planning.