• DocumentCode
    3202997
  • Title

    Empirical analysis of Competitive Coevolution Multiobjective Evolutionary Algorithm

  • Author

    Tan, Tse Guan ; Teo, Jason ; Lau, Hui Keng

  • Author_Institution
    Centre for Artificial Intell., Univ. Malaysia Sabah, Kota Kinabalu
  • fYear
    2007
  • fDate
    25-28 Nov. 2007
  • Firstpage
    501
  • Lastpage
    504
  • Abstract
    The integration between strength Pareto Evolutionary algorithm 2 (SPEA2) and competitive coevolution (CE) concept is presented in this paper, a strategy for solving an optimization problem with three scalable objectives. The Hall of Fame (HOF) competitive fitness function is used to implement the CE. This proposed algorithm referred to as SPEA2-CE-HOF. The performance between SPEA2-CE-HOF is compared against original SPEA2 in solving problems in the DTLZ suite having three to five objectives. The results showed that the SPEA2-CE-HOF performed better than SPEA2 in most of the DTLZ test problems for the generational distance. However the proposed algorithm performed average for the coverage metric.
  • Keywords
    Pareto optimisation; evolutionary computation; competitive coevolution multiobjective evolutionary algorithm; competitive fitness function; optimization; strength Pareto evolutionary algorithm; Algorithm design and analysis; Artificial intelligence; Competitive intelligence; Evolutionary computation; Genetic algorithms; Intelligent systems; Pareto analysis; Pareto optimization; Performance evaluation; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-1355-3
  • Electronic_ISBN
    978-1-4244-1356-0
  • Type

    conf

  • DOI
    10.1109/ICIAS.2007.4658439
  • Filename
    4658439