A Hybrid Improved Particle Swarm Optimization Based on Dynamic Parameters Control and Metropolis Accept Rule Strategy

@article{Shi2009AHI,
  title={A Hybrid Improved Particle Swarm Optimization Based on Dynamic Parameters Control and Metropolis Accept Rule Strategy},
  author={Ruifeng Shi and Xiangjie Liu},
  journal={2009 Third International Conference on Genetic and Evolutionary Computing},
  year={2009},
  pages={649-653}
}
Particle Swarm Optimization (PSO), a population-based intelligent modern heuristic algorithm, is inspired from the simulation of flock prayer behavior. It is vastly employed in various industrial applications due to its fast convergence and easy to carry out. Based on the analysis of current existing PSO algorithms, a Hybrid Improved PSO (HIPSO) is proposed in this paper, in which chaos initialization is introduced to improve the population diversity, and adaptive parameters' control strategy… CONTINUE READING
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