• DocumentCode
    2606218
  • Title

    Genetical swarm optimization: a new hybrid evolutionary algorithm for electromagnetics

  • Author

    Grimaldi, E.A. ; Grimaccia, F. ; Mussetta, M. ; Zich, R.E.

  • Author_Institution
    Politecnico di Milano, Dipartimento di Elettrotecnica, Piazza Leonardo da Vinci 32,20133, Milano, Italy
  • fYear
    2004
  • fDate
    14-17 Sept. 2004
  • Firstpage
    458
  • Lastpage
    460
  • Abstract
    This paper presents a new hybrid evolutionary algorithm combining Particle Swarm Optimization and Genetic Algorithms, called GSO (Genetical Swarm Optimization). GSO algorithm is essentially a population-based heuristic search technique which can be used to solve combinatorial optimization problems, modeled on the concept of natural selection but also based on cultural and social evolution. Numerical results and comparison of the different techniques are presented for an electromagnetic optimization problem.
  • Keywords
    Constraint optimization; Cultural differences; Electromagnetic modeling; Evolutionary computation; Genetic algorithms; Genetic mutations; Particle swarm optimization; Performance evaluation; Search methods; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mathematical Methods in Electromagnetic Theory, 2004. 10th International Conference on
  • Conference_Location
    Dniepropetrovsk, Ukraine
  • Print_ISBN
    0-7803-8441-5
  • Type

    conf

  • DOI
    10.1109/MMET.2004.1397080
  • Filename
    1397080