• DocumentCode
    2633095
  • Title

    Test Paper Problem Solved by Binary Ant Colony Algorithm

  • Author

    Meiying Cheng ; Xiong, Weiqing

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Ningbo Univ., Ningbo
  • fYear
    2008
  • fDate
    18-20 June 2008
  • Firstpage
    95
  • Lastpage
    95
  • Abstract
    Through analyzing the mathematical model and objective function of the composing test paper, this article abstracts that the composing test paper model is really a multi-objective linear programming model, and the binary ant colony algorithm is introduced to solve the problem. Owning to the adoption of the binary coding, each ant chooses the subject or not only need to according to the strength of the pheromone on every edge, and the requirement for the behavior of every single ant is lower, so the corresponding memory is relatively less. Experimental results demonstrate that the algorithm can solve the test paper problem quickly and effectively, and also has practical value.
  • Keywords
    education; evolutionary computation; linear programming; binary ant colony algorithm; binary coding; mathematical model; multi-objective linear programming model; objective function; Abstracts; Algorithm design and analysis; Ant colony optimization; Computer science; Convergence; Genetic algorithms; Heuristic algorithms; Linear programming; Mathematical model; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
  • Conference_Location
    Dalian, Liaoning
  • Print_ISBN
    978-0-7695-3161-8
  • Electronic_ISBN
    978-0-7695-3161-8
  • Type

    conf

  • DOI
    10.1109/ICICIC.2008.536
  • Filename
    4603284