Hybrid Ensemble Particle Swarm Optimization
Yan Shi · 2009
In this paper a hybrid ensemble particle swarm optimization (HEPSO) algorithm is presented. It combines ensemble learning, subpopulation, part dimensions and random order strategies together. Ensemble learning can help providing a more accurate global guider through combining some previous best positions (pbest) of the particles. The other three strategies increase the diversity. And this algorithm is compared with standard PSO and some other improved PSO to illustrate how HPSO can benefit from these strategies.