Particle Swarm Optimization based on the initial population of clustering

The initial population of Particle Swarm Optimization (PSO) directly concerns global convergence and searching efficiency of PSO. The reasonable setting of initial population and operational parameters is an important problem in the application of PSO to perform optimization calculation. Based on the study on how to set the initial population, such conclusion can be drawn that the initial population of PSO must reflect the information on solution space scientifically. The PSO based on the initial population of clustering is proposed. The diversity of the population was analyzed according to the discrepancy in the solution space and objective function space. The integrated clustering index, which combines the fitness value and space location, was applied to design the initial population. Simulation results show that the method is feasible and effective.