Improved adaptive particle swarm optimization algorithm based on cloud theory
Yanqiong Zhang · Jisuanji yingyong yanjiu · 2010
For the purpose of improving the basic PSO’s search performance and individual optimizing ability,speeding up the convergence,presented an adaptive particle swarm optimization based on cloud theory ( CPSO) ,relative to the basic PSO algorithm. The inertia weight was adaptively varied depending on X-conditional cloud generator. The inertia weight had the stable tendency and randomness property because of the cloud model and the distance between the particle and the current optimal position. Experimental results show CPSO can greatly improve the global convergence ability and enhance the rate of convergence.