• DocumentCode
    2912902
  • Title

    A cooperative artificial immune network with particle swarm behavior for multimodal function optimization

  • Author

    Liu, Li ; Xu, Wenbo

  • Author_Institution
    Inf. Technol. Dept., Jiangnan Univ., Wuxi
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    1550
  • Lastpage
    1555
  • Abstract
    Artificial immune network has been receiving particular attention over the last few years. Recent researches have revealed that, without stimulation and cooperation of network cells, lots of redundant explorations waste ldquoresourcesrdquo, which affects searching ability and searching speed. In this paper, a cooperative artificial immune network denoted CoAIN is devised for multimodal function optimization. To explore and exploit searching space efficiently and effectively, the interactions within the network are not only suppression but also cooperation. Network cells cooperate with particle swarm behavior making use of the best position encountered by itself and its neighbor. Numeric benchmark functions were used to assess the performance of CoAIN compared with opt-aiNet, BCA, hybrid GA, and PSO algorithms.
  • Keywords
    artificial immune systems; particle swarm optimisation; search problems; PSO algorithms; cooperative artificial immune network; multimodal function optimization; particle swarm behavior; searching ability; searching speed; Artificial immune systems; Benchmark testing; Clustering algorithms; Convergence; Genetic algorithms; Genetic mutations; Immune system; Information technology; Particle swarm optimization; Size control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4630998
  • Filename
    4630998