• DocumentCode
    618042
  • Title

    A less exploitative variation of the Enhanced Ant Colony System applied to SOP

  • Author

    Ezzat, Ahmed ; Abdelbar, Ashraf

  • Author_Institution
    Dept. of Comput. Sci. & Eng., American Univ. in Cairo, Cairo, Egypt
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    1917
  • Lastpage
    1924
  • Abstract
    The Ant Colony System (ACS) model tends to favor exploitation over exploration, relative to other Ant Colony Optimization (ACO) models. Gambardella et al. (2012) have introduced an Enhanced ACS (EACS) that is even more exploitative than ACS, and have found that EACS improves performance on several problems, including the Sequential Ordering Problem (SOP). In this paper, we propose a variation on EACS that is less exploitative than EACS, but still more exploitative than ACS. Evaluating our model on SOP, and using the same library of instances as Gambardella et al., we find that our model improves performance to a statistically significant extent.
  • Keywords
    ant colony optimisation; combinatorial mathematics; EACS; ant colony system; discrete combinatorial optimization; enhanced ACS; less exploitative variation; sequential ordering problem; Ant colony optimization; Data structures; Equations; Mathematical model; Search problems; Standards; Stochastic processes; Ant Colony System (ACS); Combinatorial Optimization; Holland´s Exploitation-Exploration Tradeoff; Sequential Ordering Problem (SOP); State Space Search; Statistical Significance; Swarm Intelligence; Wilcoxon Signed-Ranks Test;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557793
  • Filename
    6557793