• DocumentCode
    2988871
  • Title

    Research on Intelligent Auto-Generating Test Paper Based on Ant Colony Algorithm

  • Author

    Zhang Minxia ; Huang Jian

  • Author_Institution
    Dept. of Comput. Sci. & Techonolgy, Zhejiang Univ. of Technol., Hangzhou, China
  • fYear
    2009
  • fDate
    18-20 Jan. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The aim of test paper composing is to compose an optimization test paper that satisfies the parameters which the user inputs, so the test paper composing problem is a classical multi-objective linear programming problem. After analyzing the mathematical model of the test paper composing problem, this paper converted part of the restricting conditions of test paper composing problem to objective function, and introduced the ant colony algorithm to solve the problem. According to the character of test paper composing, we designed the corresponding structural map, fitness function and heuristic function, achieved a more satisfactory results using integer coding. Experiment results show that the algorithm can solve the test paper composing problem quickly, effectively and can fit the requirements of intelligent test paper generating strategy.
  • Keywords
    cooperative systems; genetic algorithms; heuristic programming; integer programming; linear programming; ant colony algorithm; fitness function; heuristic function; integer coding; intelligent auto-generating test paper; multi-objective linear programming problem; objective function; optimization test paper; structural map; test paper composing problem; Algorithm design and analysis; Ant colony optimization; Computer science; Electronic mail; Expert systems; Heuristic algorithms; Linear programming; Mathematical model; Paper technology; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5272-9
  • Type

    conf

  • DOI
    10.1109/CNMT.2009.5374675
  • Filename
    5374675