The Research of the Niche Particle Swarm Optimization Based on Self-Adaptive Radius Technology

The particle swarm optimization (PSO) first proposed by Eberhart and Kennedy, is a computational intelligence technique. The algorithm has shortcoming of premature convergence and slow convergence at the latter phase. In order to avoid these shortcomings we put forward the niche particle swarm optimization based on self-adaptive radius. This algorithm is proposed by the particle swarm optimization and Niche technology, it solves the PSO’s problem of premature convergence and slow convergence in latter phase and it improves the sharing mechanism at the role of algorithms through self-adaptive radius technology. Niche population is constituted by the particle which has the similar distance, then every particle is evolved by the PSO in each niche population, and the best individual is preserved in next generation. The algorithm is terminated until the satisfactory fitness value is found. The performance of NPSO is validated by Ackley function.