• DocumentCode
    1804281
  • Title

    An improved ant colony algorithm for vehicle shortest path problem

  • Author

    Wang, Yue ; Xue, Guoxin ; Long, Shiyu

  • Author_Institution
    School of Information Science and Engineering, Changzhou University, China
  • fYear
    2013
  • fDate
    1-8 Jan. 2013
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    An algorithm of the transition probability was studied. The model used contains several traffic parameters. Pheromone update strategy including traffic density factor was adopted. the algorithm could resolve the shortest path problem with the real-time trafic information. To avoid local minimal problem, the ant colony algorithm was combined with genetic algorithm. Compared with traditional algorithm, the results of the experimentation showed that the algorithm could find the shortest running path accurately and quickly.
  • Keywords
    Real-time systems; ant colony algorithm; real-time traffic information; shortest path problem; traffic density;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Conference Anthology, IEEE
  • Conference_Location
    China
  • Type

    conf

  • DOI
    10.1109/ANTHOLOGY.2013.6784917
  • Filename
    6784917
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1804281