• DocumentCode
    125582
  • Title

    Design and Classification of Ant Metaheuristics

  • Author

    Zufferey, Nicolas

  • Author_Institution
    HEC, Univ. of Geneva, Geneva, Switzerland
  • fYear
    2014
  • fDate
    12-14 Feb. 2014
  • Firstpage
    339
  • Lastpage
    343
  • Abstract
    Ant algorithms are well-known metaheuristics which have been widely studied and used since two decades. Generally, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. The goal of this paper is on the one hand to classify and benchmark the ant algorithms, and on the other hand to put forward the successful elements of these methods. Moreover, the performance of the different types of ant algorithms is evaluated according to several criteria, and not only according to the quality of the obtained solutions.
  • Keywords
    ant colony optimisation; ant metaheuristics algorithm; constructive ant algorithms; Algorithm design and analysis; Classification algorithms; Equations; Force; Heuristic algorithms; Optimization; Robustness; ant algorithms; population-based metaheuristics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel, Distributed and Network-Based Processing (PDP), 2014 22nd Euromicro International Conference on
  • Conference_Location
    Torino
  • ISSN
    1066-6192
  • Type

    conf

  • DOI
    10.1109/PDP.2014.69
  • Filename
    6787296