• DocumentCode
    618039
  • Title

    An Ant Colony System algorithm for automatically schematizing transport network data sets

  • Author

    Ware, Matthew ; Richards, Nigel

  • Author_Institution
    Fac. of Adv. Technol., Univ. of South Wales, Pontypridd, UK
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    1892
  • Lastpage
    1900
  • Abstract
    The work presented here investigates the usefulness of Ant Colony Optimisation to solving network schematization problems. This is a well-established problem domain and a number of solutions have appeared in the literature previously. In this paper an Ant Colony System (ACS) based algorithm is presented, together with experimental results and performance analysis. The aim is to provide an algorithm that produces better results and is more efficient (in terms of execution times) than previous solutions. Throughout the paper, ACS is tested and evaluated empirically - that is, experiments are performed and observed, these observations are recorded and subsequently analysed. In order to perform the experiments, a software implementation of the algorithm is constructed and then applied to test data sets. No attempt has been made here to perform a theoretical analysis of ACS. The results presented demonstrate that ACS can be used as an effective means of providing solutions to network schematization problems. In particular, ACS is shown to outperform a previous Simulated Annealing based solution.
  • Keywords
    ant colony optimisation; cartography; ACS based algorithm; ant colony system algorithm; automated cartography; network schematization problems; software implementation; transport network data sets; Algorithm design and analysis; Approximation methods; Cities and towns; Joining processes; Layout; Simulated annealing; ant colony optimization; automated cartography; metro maps;
  • 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.2013.6557790
  • Filename
    6557790