• DocumentCode
    2559618
  • Title

    Heuristic Algorithms for Capacity flexibility of urban transit networks

  • Author

    Hang, Zhao ; Binglei, Xie ; Shi, An

  • Author_Institution
    Res. Center of Traffic Eng., Harbin Inst. of Technol., Shenzhen, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1186
  • Lastpage
    1190
  • Abstract
    In this paper, the concept of capacity flexibility is introduced into transit network, and the model of capacity flexibility of urban transit networks is formulated. A heuristic solution based on hybrid genetic algorithm is proposed to the model. GA-LS (Genetic algorithms with Local search) is applied to solve the model. It is also tested by a numerical example with a small transit network. The results show how the maximum additional passenger flows from each origin-destination (OD) pair are determined in a transit network and what extent the transit network supply meets the additional passenger demand in a certain level of service. These results show that the GA-LS method considerably improves the value of the objective function for same iterative times compared with the general GA, but spending more time.
  • Keywords
    genetic algorithms; search problems; transportation; GA-LS; OD; genetic algorithms with local search; heuristic algorithms; hybrid genetic algorithm; maximum additional passenger flows; objective function; origin-destination pair; small transit network; urban transit network capacity flexibility; Biological cells; Educational institutions; Genetic algorithms; Numerical models; Roads; Vehicles; Capacity flexibility; Genetic algorithms; Local search; Transit networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2012 Eighth International Conference on
  • Conference_Location
    Chongqing
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4577-2130-4
  • Type

    conf

  • DOI
    10.1109/ICNC.2012.6234694
  • Filename
    6234694