• DocumentCode
    1642914
  • Title

    Multi-objective evolutionary programming without non-domination sorting is up to twenty times faster

  • Author

    Qu, B.Y. ; Suganthan, P.N.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
  • fYear
    2009
  • Firstpage
    2934
  • Lastpage
    2939
  • Abstract
    In this paper, multi-objective evolutionary programming (MOEP) using fuzzy rank-sum with diversified selection is introduced. The performances of this algorithm as well as MOEP with non-domination sorting on the set of benchmark functions provided for CEC2009 Special Session and competition on Multi-objective Optimization are reported. With this rank-sum sorting and diversified selection, the speed of the algorithm has increased significantly, in particular by about twenty times on five objective problems when compared with the implementation using the non-domination sorting. Beside this, the proposed approach has performed either comparable or better than the MOEP with non-domination sorting.
  • Keywords
    evolutionary computation; fuzzy set theory; CEC2009 Special Session; diversified selection; fuzzy rank-sum; multiobjective evolutionary programming; Artificial intelligence; Evolutionary computation; Genetic programming; Random number generation; Sorting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983312
  • Filename
    4983312