Adaptive particle swarm optimization algorithm

The social behavior of swarm is a balance between complete order and total chaos, Therefore, the level of randomness in the group is an important factor. Firstly, the concept of chaos is introduced to the particle swarm optimization (PSO) by adding a durative random item representing principle of adaptability of swarm intelligence. Then, particles with small probability will fly to the center of the swarm, which is introduced to balance the order and random behaviour. The essence of adaptive particle swarm optimization (APSO) is that the inscrutable decision on the rational behavior is introduced to order decision, and the complex behaviour of socical swarm is simulated. Experimental simulations show that the proposed method can improve the stability of convergence effectively.