• DocumentCode
    2916323
  • Title

    Decentralised distributed multiple objective particle swarm optimisation using peer to peer networks

  • Author

    Scriven, Ian ; Lewis, Andrew ; Ireland, David ; Lu, Junwei

  • Author_Institution
    Sch. of Eng., Griffith Univ., Brisbane, QLD
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    2925
  • Lastpage
    2928
  • Abstract
    This paper describes a distributed particle swarm optimisation algorithm (PSO) based on peer-to-peer computer networks. A number of modifications are made to the more traditional synchronous PSO algorithm to allow for fully decentralised, scalable and fault-tolerent operation. The modified algorithm uses staggered propagation of objective-space knowledge between sub-swarms to eliminate the need for a centralised data store. Analytical test functions are used to examine the performance of the proposed algorithm and its variations in comparison with a basic synchronous PSO implementation. The results clearly show the feasibility of decentralised particle swarm optimisation.
  • Keywords
    multivariable systems; particle swarm optimisation; peer-to-peer computing; decentralised distributed multiple objective particle swarm optimisation; fault-tolerent operation; objective-space knowledge; peer-to-peer computer networks; staggered propagation; Algorithm design and analysis; Computer networks; Distributed computing; Genetic algorithms; Grid computing; Master-slave; Particle swarm optimization; Peer to peer computing; Performance analysis; Testing;
  • 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.2008.4631191
  • Filename
    4631191