• DocumentCode
    2337182
  • Title

    A novel hybrid algorithm for global optimization based on EO and SFLA

  • Author

    Luo, Jianping ; Chen, Min-Rong ; Li, Xia

  • Author_Institution
    Coll. of Inf. Eng., Shenzhen Univ., Shenzhen, China
  • fYear
    2009
  • fDate
    25-27 May 2009
  • Firstpage
    1935
  • Lastpage
    1939
  • Abstract
    In this study, we have presented a new hybrid optimization method, called hybrid shuffled frog leaping algorithm and extremal optimization algorithm (SFLA-EO) which introduces EO to SFLA. SFLA-EO combines the merits of both SFLA and EO by drawing on the local-search strategy from EO and global-search strategy from SFLA. The results of experiments carried out with six well-known benchmark functions have shown the proposed algorithm possesses outstanding performance in convergence speed, robustness and stability, as compared to standard PSO, SFLA and EO. It is proved that the SFLA-EO algorithm is very effective and superior to solve continuous global optimization problems.
  • Keywords
    optimisation; search problems; SFLA-EO; extremal optimization algorithm; global optimization; global-search strategy; local-search strategy; shuffled frog leaping algorithm; Biological system modeling; Convergence; Cost function; Educational institutions; Evolution (biology); Genetic mutations; Optimization methods; Particle swarm optimization; Physics; Robust stability; Extremal optimization; Global optimization; Particle swarm optimization; Shuffled frog leaping algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-2799-4
  • Electronic_ISBN
    978-1-4244-2800-7
  • Type

    conf

  • DOI
    10.1109/ICIEA.2009.5138540
  • Filename
    5138540