An improved partial swarm optimization algorithm for solving nonlinear equation problems

Aim at solving nonlinear equations problem, an improved Evolutionary Algorithms was proposed. The algorithm was based on standard PSO (particle swarm optimization algorithm) and the sections of initial particles. At the same time, for the purpose of ensuring global optimum, the Heuristic search field was applied to jump out of the local optima. In order to prove the validity of the algorithm, the three typical examples of nonlinear equations were chosen, and the different parameters were applied to experiment. At last the results were to indicate that, the improved PSO algorithm was simple, efficient and can obtain all solutions once, and it was worthy method to be extended for solving nonlinear equations.