A Particle Swarm Optimization with an Improved Updating Strategy

In this paper, we introduce a novel pbest updating strategy to improve the achievement of the original particle swarm algorithm (PSO). First, we set a threshold for using our proposed updating strategy for pbest. Then if the algorithm reaches the condition of using this threshold, we select a pbest with an excellent performance in the population to search in a local valuable region for improving the precise search of particles. Meanwhile, we also select a pbest with a worse performance to search in the entire solution space for improving the global search ability of particles. By comparing with the traditional PSO and its variants on benchmark functions, the PSO algorithm with a novel pbest updating strategy (PPSO) performs much better than the other compared algorithms.