Multi-optimum programming based particle swarm optimization algorithm and its application in multi-dimensional multi-modal function optimization

摘要

In this paper, the knowledge of multi-optimum distribution state is introduced into general programming of the particle swarm movement to avoid falling into local optimums at the original stage of the computation. The algorithm is improved based on the modified particle algorithm and used to optimize the multi-dimensional and multi-optimum function. Simulation results show that, the general convergence character of the algorithm derived in this paper has better performance than the results derived based on the modified particle algorithm.