A Novel Particle Swarm Optimization Algorithm Model with Centroid and its Application

In order to enhance inter-particle cooperation and information sharing capabilities, an improved particle swarm algorithm optimization model is proposed by introducing the centroid of particle swarm in the standard PSO model to improve global optimum efficiency and accuracy of algorithm, then parameter selection guidelines are derived in the convergence of new algorithm. The results of Benchmark function simulation and the material balance computation (MBC) in alumina production show the new algorithm, with both a steady convergence and a better stability, not only enhance the local searching efficiency and global searching performance greatly, but also have faster higher precision and convergence speed, and can avoid the premature convergence problem effectively.