• DocumentCode
    167558
  • Title

    Improved quantum ant colony algorithm for solving TSP problem

  • Author

    Ma Ying ; Tian Wei-jian ; Fan Yang-yu

  • Author_Institution
    Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2014
  • fDate
    8-9 May 2014
  • Firstpage
    453
  • Lastpage
    456
  • Abstract
    For the low efficiency and poor performance of the ant colony algorithm in solving TSP problems, a new quantum ant colony algorithm proposed. The models of probability selection and pheromone are redefined, integrated with the quantum information intensity factor; The factor updated by quantum rotating gate according to iteration process; Some important parameters are self-adapted controlled at the same time; And 3-opt is used to further local optimization. Stimulation shows the performance is greatly improved.
  • Keywords
    ant colony optimisation; iterative methods; probability; quantum computing; travelling salesman problems; TSP problem; iteration process; pheromone; probability selection; quantum ant colony algorithm; quantum information intensity factor; quantum rotating gate; Computational modeling; Convergence; Educational institutions; Optimized production technology; Quality of service; Robustness; Search problems; TSP; quantum ant colony algorithm; quantum computing; quantum evolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Computer and Applications, 2014 IEEE Workshop on
  • Conference_Location
    Ottawa, ON
  • Type

    conf

  • DOI
    10.1109/IWECA.2014.6845654
  • Filename
    6845654