• DocumentCode
    3660459
  • Title

    Adaptive ant colony algorithm based on cloud model

  • Author

    Zhengyan Liu;Jieli Jiang;Ying Yang;Shibing Wang

  • Author_Institution
    School of computer and information engineering, Fuyang Teachers College, Anhui Province, China
  • fYear
    2015
  • Firstpage
    2654
  • Lastpage
    2657
  • Abstract
    To overcome the slow convergence and local optimum of ant colony algorithm, the cloud model theory is adopted to regulate reasonably the randomness of the ant colony algorithm. In this paper, several adaptive strategies are proposed for the parameters of the ant colony algorithm and the cloud model, and for the optimum path determination. Meanwhile, the evaluation algorithm of pheromone distribution is proposed. Simulation results for multiple TSP validate the efficiency and stability of the proposed algorithm.
  • Keywords
    "Adaptation models","Algorithm design and analysis","Convergence","Computers","Computational modeling","Traveling salesman problems","Generators"
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICInfA.2015.7279733
  • Filename
    7279733
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3660459