• DocumentCode
    1637789
  • Title

    Hybridizing PSO and DE for improved vector evaluated multi-objective optimization

  • Author

    Grobler, Jacomine ; Engelbrecht, Andries P.

  • Author_Institution
    Dept. of Ind. & Syst. Eng., Univ. of Pretoria, Pretoria
  • fYear
    2009
  • Firstpage
    1255
  • Lastpage
    1262
  • Abstract
    This paper introduces a new vector evaluated multi-objective optimization algorithm. The vector evaluated differential evolution particle swarm optimization (VEDEPSO) algorithm is a hybridization of the classical vector evaluated particle swarm optimization (VEPSO) and vector evaluated differential evolution (VEDE) algorithms of Parsopoulos et. al. Comparisons of VEDEPSO with respect to VEPSO and VEDE on a well known multi-objective benchmark problem set indicated that significant performance improvements can be attributed to the VEDEPSO algorithm.
  • Keywords
    evolutionary computation; particle swarm optimisation; PSO; differential evolution; particle swarm optimization; vector evaluated multiobjective optimization; Algorithm design and analysis; Computer industry; Computer science; Costs; Decision making; Functional analysis; Optimization methods; Particle swarm optimization; Performance analysis; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983089
  • Filename
    4983089