• DocumentCode
    2461268
  • Title

    Extension of Max-Min Ant System with Exponential Pheromone Deposition Rule

  • Author

    Acharya, Ayan ; Maiti, Deepyaman ; Banerjee, Aritra ; Janarthanan, R. ; Konar, Amit

  • Author_Institution
    Dept. of Electron. & Telecommun. Eng., Jadavpur Univ., Kolkata
  • fYear
    2008
  • fDate
    14-17 Dec. 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    The paper presents an exponential pheromone deposition approach to improve the performance of classical ant system algorithm which employs uniform deposition rule. A simplified analysis using differential equations is carried out to study the stability of basic ant system dynamics with both exponential and constant deposition rules. A roadmap of connected cities, where the shortest path between two specified cities are to be found out, is taken as a platform to compare max-min ant system model (an improved and popular model of ant system algorithm) with exponential and constant deposition rules. Extensive simulations are performed to find the best parameter settings for non-uniform deposition approach and experiments with these parameter settings revealed that the above approach outstripped the traditional one by a large extent in terms of both solution quality and convergence time.
  • Keywords
    artificial intelligence; differential equations; minimax techniques; differential equation; exponential pheromone deposition rule; max-min ant system; Advisory Committee; Ant colony optimization; Circuits; Cities and towns; Closed-form solution; Difference equations; Differential equations; Educational institutions; Stability analysis; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computing and Communications, 2008. ADCOM 2008. 16th International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4244-2962-2
  • Electronic_ISBN
    978-1-4244-2963-9
  • Type

    conf

  • DOI
    10.1109/ADCOM.2008.4760419
  • Filename
    4760419