Application of Simulated Annealing Particle Swarm Optimization Algorithm in Power Coal Blending Optimization

The particle swarm optimization algorithm is easily trapped into local optimization. In order to improve its performance, The simulated annealing operation was introduced into PSO. The hybrid algorithm combines the fast search optimum ability of PSO with probability jump property of SA. It can maintain the individual diversity and restrain the degenerate phenomenon. The experiment results compared with genetic algorithm demonstrate that the proposed algorithm can search for global optimal solution more reliably and faster, and the power coal blending optimization can be efficiently solved with higher quality.