• DocumentCode
    170372
  • Title

    ELA: A new swarm intelligence algorithm

  • Author

    Yaosheng Sun ; Zhangcan Huang ; Yu Chen

  • Author_Institution
    Sch. of Sci., Wuhan Univ. of Technol., Wuhan, China
  • fYear
    2014
  • fDate
    16-18 May 2014
  • Firstpage
    109
  • Lastpage
    113
  • Abstract
    By analyzing the living behaviors of eels, this paper proposes a new eel swarm intelligence algorithm. This paper first describes the behavior of migratory eels, extracts three important behaviors-density adaption, neighboring learning and sex mutation, and establishes a model for the mathematical description of the three important behaviors. Based on rational organization of the three important behaviors, the eel algorithm is designed for continuous optimization problems. Finally, we test the performance of eel swarm intelligence algorithm via several selected benchmark problems. The results show that the algorithm, in terms of its excellent convergence speed and solving accuracy, is competitive to the compared algorithms.
  • Keywords
    biology computing; optimisation; swarm intelligence; ELA; behaviors-density adaption; mathematical description; migratory eels; neighboring learning; optimization problems; rational organization; sex mutation; swarm intelligence algorithm; Algorithm design and analysis; Benchmark testing; Optimization; Particle swarm optimization; Signal processing algorithms; Sociology; Statistics; continuous algorithm; heuristic search algorithms; migration behavior; optimization problem; swarm intelligence algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Progress in Informatics and Computing (PIC), 2014 International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4799-2033-4
  • Type

    conf

  • DOI
    10.1109/PIC.2014.6972306
  • Filename
    6972306