• DocumentCode
    1951155
  • Title

    The Thermodynamic Particle Swarm Optimizer

  • Author

    Wu Yu ; Li Yuanxiang ; Xu Xing ; Peng Shen

  • Author_Institution
    Key Lab. of Software Eng., Wuhan Univ., Wuhan
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    1203
  • Lastpage
    1206
  • Abstract
    This paper has presented a novel optimization algorithm - thermodynamic particle swarm optimizers (TDPSO). It combines the simplified evolutionary equation and the thermodynamically strategy.The simplified equation without the velocity variable has drastically reduced computation costs to achieve faster convergence. Inspired by the free energy principle of the thermo-dynamical theoretics, TDPSO algorithm has defined the rating-based entropy (RE)concept and a component thermodynamic replacement(CTR) rule. These definitions are applied to control the optimal process and to achieve the potential of finding a global optimum. Compared with other improved PSO techniques, the experimental results describe how-to make the TDPSO benefit from the thermodynamics.
  • Keywords
    entropy; evolutionary computation; particle swarm optimisation; thermodynamics; TDPSO; component thermodynamic replacement; evolutionary equation; novel optimization algorithm; rating-based entropy; thermo-dynamical theoretics; thermodynamic particle swarm optimizer; Clustering algorithms; Computer science; Equations; Optimal control; Particle swarm optimization; Process control; Simulated annealing; Software engineering; Testing; Thermodynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.1248
  • Filename
    4721969