Incorporate Energy Strategy into Particle Swarm Optimizer Algorithm Incorporate Energy Strategy into Particle Swarm Optimizer Algorithm

Incorporate Energy Strategy into Particle Swarm Optimizer Algorithm

  • 期刊名字:东华大学学报(英文版)
  • 文件大小:
  • 论文作者:ZHANG Lun,DONG De-cun,LU Yan,C
  • 作者单位:College of Transportation Engineering
  • 更新时间:2022-11-28
  • 下载次数:
论文简介

The issue of optimizing the dynamic parameters in Particle Swarm Optimizer (PSO) is addressed in this paper.An algorithm is designed which makes all particles originally endowed with a certain level energy, what here we define as EPSO (Energy Strategy PSO).During the iterative process of PSO algorithm, the Inertia Weight is updated according to the calculation of the particle's energy.The portion ratio of the current residual energy to the initial endowed energy is used as the parameter Inertia Weight which aims to update the particles' velocity efficiently.By the simulation in a graph theoritical and a functional optimization problem respectively, it could be easily found that the rate of convergence in EPSO is obviously increased.

论文截图
版权:如无特殊注明,文章转载自网络,侵权请联系cnmhg168#163.com删除!文件均为网友上传,仅供研究和学习使用,务必24小时内删除。