Improved particle swarm optimization

Abstract

To improve the searchingperformance of particle swarm optimization,inaccordance with problems of the too strong stochastic characteristic and slow convergence speed of the traditional particleswarm optimization.Two new position update equations are proposed byusing the strategy of extrapolation in mathematics.Thus,a new class of particleswarm optimization with induction-enhanced is given.The induction is made to updating particle's position by the new arithmetic in order to decreasing the randomicity of particle swarm opti-mization and improve the efficiency of searching.Four benchmarks function are tested and show that the new algorithm is better than the traditional particle swarm optimization with both a better stability and a steady convergence.