• DocumentCode
    3517456
  • Title

    An Exploration Technique for the Interacted Multiple Ant Colonies Optimization Framework

  • Author

    Aljanaby, Alaa ; Ku-Mahamud, Ku Ruhana ; Norwawi, Norita Md

  • Author_Institution
    Coll. of Arts & Sci., Univ. Utara Malaysia, Sintok, Malaysia
  • fYear
    2010
  • fDate
    27-29 Jan. 2010
  • Firstpage
    92
  • Lastpage
    95
  • Abstract
    Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. In this framework several colonies of artificial ants are utilized. These colonies are working cooperatively to solve an optimization problem using some interaction technique. Exploration technique is doing an essential job in this framework. This technique is responsible for directing the activity of utilized colonies towards the different parts of the huge search space. This paper describes the newly proposed IMACO framework and proposes an effective exploration technique. Computational tests show that the new exploration technique can furthermore improve the IMACO performance. These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system.
  • Keywords
    minimax techniques; ant colony system; exploration technique; interacted multiple ant colonies optimization framework; max-min ant system; optimization problem; search space; Ant colony optimization; Art; Artificial intelligence; Educational institutions; Insects; Intelligent systems; Particle swarm optimization; Routing; System testing; Traveling salesman problems; ant colony optimization; combinatorial optimization problems; exploitation; exploration; search stagnation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems, Modelling and Simulation (ISMS), 2010 International Conference on
  • Conference_Location
    Liverpool
  • Print_ISBN
    978-1-4244-5984-1
  • Type

    conf

  • DOI
    10.1109/ISMS.2010.28
  • Filename
    5416116