The particle swarm optimization with division of work strategy

The particle swarm optimization (PSO) method was originally designed by Kennedy and Eberhart in 1995 and has been applied successfully to various optimization problems. The PSO idea is inspired by natural concepts such as fish schooling, bird flocking and human social relations. Some experimental results show that PSO has greater "global search" ability, but the "local search" ability around the optimum is not very good. This paper analyses the PSO method and presents the improved method, which is PSO with division of work (PSOwDOW). In order to enhance the \´local search" ability of PSO we divide the particle swarm into three sub swarms and each sub swarm has a different job in PSOwDOW. Experimental results show that PSOwDOW can overcome the deficiencies in the traditional PSO and reinforce the optimizing ability of the particle swarm.