• DocumentCode
    3323544
  • Title

    Evolutionary Algorithms with Particle Swarm Movements

  • Author

    Miranda, Vladimiro

  • Author_Institution
    INESC Comput., Porto
  • fYear
    2005
  • fDate
    6-10 Nov. 2005
  • Firstpage
    6
  • Lastpage
    21
  • Abstract
    This text introduces a family of evolutionary algorithms named EPSO $evolutionary particle swarm optimization. EPSO algorithms are evolutionary methods that borrow the movement rule from particle swarm optimization methods (PSO) and use it as a recombination operator that evolves under the pressure of selection. This hybrid approach builds up an algorithm that, in several cases, in application to complex problems in power systems, has already proven to be more efficient, accurate and robust than classical evolutionary methods or classical PSO. The text presents the description of the method, didactic examples and examples of applications in real world problems
  • Keywords
    evolutionary computation; particle swarm optimisation; evolutionary algorithm; evolutionary particle swarm optimization; particle swarm movement; power systems; recombination operator; Ant colony optimization; Evolution (biology); Evolutionary computation; Genetic algorithms; Hybrid power systems; Neural networks; Optimization methods; Particle swarm optimization; Robustness; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    1-59975-174-7
  • Type

    conf

  • DOI
    10.1109/ISAP.2005.1599236
  • Filename
    1599236