• DocumentCode
    2864022
  • Title

    Solving the Travelling Salesman Problem by the Program of Ant Colony Algorithm

  • Author

    Zhu Ju-fang ; Li Qing-yuan

  • Author_Institution
    Chinese Acad. of Surveying & Mapping, Chinese Univ. of Min. & Technol., Beijing, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Ant colony algorithm is a novel simulated ecosystem evolutionary algorithm, which is applied to solving complex combinatorial optimization problems. The basic principle and realization about ant colony algorithm are studied in this paper. The algorithm is realized under the Visual C++ compiler environment, and applied to solving the travelling salesman problem (TSP). The result is accordance with the best route solution. This algorithm has practical worth.
  • Keywords
    evolutionary computation; program compilers; travelling salesman problems; Visual C++ compiler; ant colony algorithm; complex combinatorial optimization problems; simulated ecosystem evolutionary algorithm; travelling salesman problem; Ant colony optimization; Cities and towns; Ecosystems; Evolutionary computation; Genetic algorithms; Heuristic algorithms; Mathematical model; Neural networks; Robustness; Traveling salesman problems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5366235
  • Filename
    5366235