• DocumentCode
    3515239
  • Title

    Solving Multi-objective Optimization Problems with Chaotic Ant Swarm

  • Author

    Han, Renmin ; Huang, Jun ; Wang, Junping ; Guo, Danqing

  • Author_Institution
    Sch. of software, Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2010
  • fDate
    28-29 Oct. 2010
  • Firstpage
    83
  • Lastpage
    87
  • Abstract
    Chaotic Ant Swarm is a recently new and promising algorithm of Optimization Problem based on the chaotic theory and foraging food processing of ants. This paper proposes a Multi-Objective Optimization version of CAS, named MOCAS, by changing the colony behavior organization. The proposed algorithm also introduced a re-distribution operation that ensures the uniform distribution of final result. We have validated it by several test functions taken from the standard literature. The results are exciting and show the competitiveness in multi-objective optimization.
  • Keywords
    chaos; optimisation; MOCAS; chaotic ant swarm; chaotic theory; colony behavior organization; multiobjective optimization problem; optimization problem; Chaos; Equations; Mathematical model; Neodymium; Optimization; Organizations; Proposals; Chaotic Ant Swarm; Pareto-optimal solutions; multiobjective optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence Information Processing and Trusted Computing (IPTC), 2010 International Symposium on
  • Conference_Location
    Huanggang
  • Print_ISBN
    978-1-4244-8148-4
  • Electronic_ISBN
    978-0-7695-4196-9
  • Type

    conf

  • DOI
    10.1109/IPTC.2010.9
  • Filename
    5663176