• DocumentCode
    2214644
  • Title

    Immune clone algorithm and mfcTP

  • Author

    Hongwei, Zhang ; Xiaoke, Cui ; Shurong, Zou

  • Author_Institution
    Sch. of Comput. Sci., Chengdu Univ. of Inf. Technol., Chengdu, China
  • Volume
    1
  • fYear
    2010
  • fDate
    20-22 Aug. 2010
  • Abstract
    A new immune clone algorithm is proposed for coping with the multi-objective fixed-charged transportation optimization problem (mfcTP) in the paper. In terms of this new algorithm base on the vector affinity, we firstly make the sum of active and fixed-charged order by ascending and greedy algorithm infused into the antibody decoding, sequentially enhancing the intelligent learning ability of antibody; Then apply the cloning mechanism, balanced the relationship between the global exploration and the local development and enhanced the optimization ability of the algorithm. The experimental results show that the algorithm can find better Pareto front and Pareto optimal solutions in the real-world problems even if nonlinear and discontinuous. So it is more effective than st-GA and m-GA.
  • Keywords
    Pareto optimisation; artificial immune systems; greedy algorithms; transportation; vectors; Pareto front; Pareto optimal solutions; active order; antibody decoding; ascending algorithm; cloning mechanism; fixed-charged order; greedy algorithm; immune clone algorithm; mfcTP optimization; multiobjective fixed-charged transportation optimization; vector affinity; Production facilities; Pareto optimal solutions; Pruefer number; concentration; immune clone; vector affinity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2154-7491
  • Print_ISBN
    978-1-4244-6539-2
  • Type

    conf

  • DOI
    10.1109/ICACTE.2010.5578982
  • Filename
    5578982