Double Coordinate Many Particle Swarm Optimization Algorithm

This paper proposes a particle swarm optimization algorithm (DC-PSO) which has double group of coordination mechanism that focus on remedy the limitation of particle swarm algorithm(PSO) with low efficiency and poor stability because of the lack of diversity. This particle swarm optimization algorithm includes multiple lower work and upper decision particle swarm. The lower work particle swarm is to do the information acquisition and iteration calculation, while the top particle swarm processes information and decision-making information feedback, and double particle swarm do the teamwork. At the same time, acceleration factor with increasing distribution exponential function controls the coupling among particle swarm, so as to improve the efficiency and stability of the particle swarm when they doing the search job. The result of simulation experiment shows the effectiveness and superiority of particle swarm optimization algorithm in solving the function optimization problem.