Example-based learning particle swarm optimization for continuous optimization

@article{Huang2012ExamplebasedLP,
  title={Example-based learning particle swarm optimization for continuous optimization},
  author={Han Huang and Hu Qin and Zhifeng Hao and Andrew Lim},
  journal={Inf. Sci.},
  year={2012},
  volume={182},
  pages={125-138}
}
Particle swarm optimization (PSO) is a heuristic optimization technique based on swarm intelligence that is inspired by the behavior of bird flocking. The canonical PSO has the disadvantage of premature convergence. Several improved PSO versions do well in keeping the diversity of the particles during the searching process, but at the expense of rapid convergence. This paper proposes an example-based learning PSO (ELPSO) to overcome these shortcomings by keeping a balance between swarm… CONTINUE READING