• DocumentCode
    2245639
  • Title

    Differential Evolution with a local search operator

  • Author

    Gu, Jirong ; Gu, Guojun

  • Author_Institution
    Geogr. & Resources Sci. Coll., Sichuan Normal Univ., Chengdu, China
  • Volume
    2
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    480
  • Lastpage
    483
  • Abstract
    Differential Evolution (DE) is a population-based stochastic search algorithm, which has shown good performance in many optimization problems. In this paper, we propose an improved DE algorithm, called LSDE, by using a local search operator to enhance the performance of classical DE. In order to verify the performance of LSDE, we test the proposed approach on seven well-known benchmark problems. The simulation results show that LSDE obtains good performance and outperforms the classical DE in all test cases.
  • Keywords
    evolutionary computation; optimisation; search problems; stochastic processes; differential evolution; local search operator; optimization problems; stochastic search algorithm; Asia; Automatic control; Chromium; Electronic design automation and methodology; Evolutionary computation; Fuzzy logic; Genetic algorithms; Genetic mutations; Robotics and automation; Testing; differential evolution (DE); evolutionary computation; global optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
  • Conference_Location
    Wuhan
  • ISSN
    1948-3414
  • Print_ISBN
    978-1-4244-5192-0
  • Electronic_ISBN
    1948-3414
  • Type

    conf

  • DOI
    10.1109/CAR.2010.5456601
  • Filename
    5456601