Feedback learning particle swarm optimization

@article{Tang2011FeedbackLP,
  title={Feedback learning particle swarm optimization},
  author={Yang Tang and Zidong Wang and Jian-An Fang},
  journal={Appl. Soft Comput.},
  year={2011},
  volume={11},
  pages={4713-4725}
}
In this paper, a feedback learning particle swarm optimization algorithm with quadratic inertia weight (FLPSOQIW) is developed to solve optimization problems. The proposed FLPSO-QIW consists of four steps. Firstly, the inertia weight is calculated by a designed quadratic function instead of conventional linearly decreasing function. Secondly, acceleration coefficients are determined not only by the generation number but also by the search environment described by each particle’s history best… CONTINUE READING