• DocumentCode
    3176444
  • Title

    A multiple ant colonies optimization algorithm based on immunity for solving TSP

  • Author

    Xue, Hongquan ; Hang, Peng Z. ; Ang, Lm Y.

  • Author_Institution
    Sch. of Econ. & Manage., Xi´´an Univ. of Technol., Xi´´an, China
  • fYear
    2010
  • fDate
    29-30 Oct. 2010
  • Firstpage
    289
  • Lastpage
    293
  • Abstract
    The traveling salesman problem (TSP) is a wellknown NP-hard problem and extensively studied problems in combinatorial optimization. Ant colony optimization algorithm (ACOA) has been used to solve many optimization problems in various fields of engineering. In this paper, a new algorithm was presented for solving TSP using ACOA based on immunity and multiple ant colonies. The new algorithm was tested on benchmark problems from TSPLIB and the test results were presented. The experimental results show that the new algorithm effectively relieves the tensions such as the premature, the convergence and the stagnation.
  • Keywords
    computational complexity; travelling salesman problems; NP-hard problem; ant colonies optimization algorithm; ant colony optimization algorithm; combinatorial optimization; traveling salesman problem; Propulsion; Ant Colony Optimization; Immune Algorithm; Immune Multiple Ant Colonies Algorithm; Multiple Ant Colonies; Traveling Salesman Problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Education (ICAIE), 2010 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-6935-2
  • Type

    conf

  • DOI
    10.1109/ICAIE.2010.5641516
  • Filename
    5641516