A Parallel Chaos Particle Swarm Optimization
Yang Dao Ping, Kai Zhang, Fan Lin Bo, Zhao Ming · 2009
To solve Particle Swarm Optimization (PSO) to plunge into the local extremums, this paper introduces parallel calculation and chaos operator and puts forward a parallel chaos particle swarm optimization. This method divides particle population into subpopulations for asynchronous and parallel chaos optimization. So it improves the search speed and keeps population diversity to avoid premature. The simulation results show this method is better than PSO.