• DocumentCode
    2071613
  • Title

    An improved Time Adaptive Ant System

  • Author

    Paul, A. ; Mukhopadhyay, Saibal

  • Author_Institution
    Camellia Inst. of Technol., Electron. & Commun. Eng., Kolkata, India
  • fYear
    2012
  • fDate
    17-19 Dec. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Time Adaptive Ant System (TAAS) is the new proposed algorithm with modified pheromone updation rule. Here, we have exploited the properties of Time adaptive Least Mean Square (LMS) algorithm for the pheromone updation rule to resolve the basic shortcoming of easily falling into local optima and slow convergence speed. The improved algorithm has better global search ability and good convergence speed. A block diagram representation is also proposed, which may leads to stability analysis. Our algorithm is applied to Traveling Salesman Problem (TSP), and the simulation shows the effective results, as compared to other existing approaches.
  • Keywords
    ant colony optimisation; convergence; evolutionary computation; least mean squares methods; search problems; travelling salesman problems; LMS algorithm; TAAS; TSP; adaptive least mean square algorithm; block diagram representation; convergence speed; global search ability; local optima; modified pheromone updation rule; stability analysis; time adaptive ant system; traveling salesman problem; Ant System; Time Adaptive Ant System; Time Adaptive LMS Algorithm; Travelling Salesman Problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers and Devices for Communication (CODEC), 2012 5th International Conference on
  • Conference_Location
    Kolkata
  • Print_ISBN
    978-1-4673-2619-3
  • Type

    conf

  • DOI
    10.1109/CODEC.2012.6509352
  • Filename
    6509352