• DocumentCode
    524936
  • Title

    Constrained optimization with Election campaign algorithm

  • Author

    Xie, Qinghua ; Lv, Wenge ; Liu, Zhiyong ; Zhang, Xiangwei ; Luo, Shaoming ; Cheng, Siyuan

  • Author_Institution
    Fac. of Electro-Mech. Eng., Guangdong Univ. of Technol., Guangzhou, China
  • Volume
    1
  • fYear
    2010
  • fDate
    30-31 May 2010
  • Firstpage
    370
  • Lastpage
    373
  • Abstract
    In this paper, we present a new method using Election campaign algorithm (ECA) combining with the dynamic penalty method to solve the nonlinear constrained optimization problems. The proposed approaches are validated using several examples taken from the optimization literature, and our results are compared with those obtained by particle swarm optimization algorithm (PSO). Our comparative study indicates that ECA verifies its good performance when dealing with constrained optimization problems with constraints.
  • Keywords
    Automation; Constraint optimization; Design engineering; Design optimization; Functional programming; Heuristic algorithms; Mechatronics; Nominations and elections; Particle swarm optimization; Voting; constrained minimum likelihood; constrained optimization; dynamic penalty method; election campaign algorithm; nonlinear constraints; optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Mechatronics and Automation (ICIMA), 2010 2nd International Conference on
  • Conference_Location
    Wuhan, China
  • Print_ISBN
    978-1-4244-7653-4
  • Type

    conf

  • DOI
    10.1109/ICINDMA.2010.5538132
  • Filename
    5538132