• DocumentCode
    3209768
  • Title

    Solving multi-class traffic assignment problem with genetic algorithm

  • Author

    Zhang, Guoqiang ; Chen, Jun

  • Author_Institution
    Transp. Coll., Southeast Univ., Nanjing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    13-14 Sept. 2010
  • Firstpage
    229
  • Lastpage
    232
  • Abstract
    Multi-class traffic assignment problem is an extension of the classic static traffic assignment problem with user equilibrium. It provides a more correct and detailed description of traffic patterns and trends. Because of the complexity of the models for multi-class traffic assignment problem, which are usually defined by a non-monotonic cost operator, neither the uniqueness nor the stability of a feasible solution can be guaranteed and the traditional nonlinear optimization algorithms are therefore invalid. Based upon the mathematic characteristics of multiclass traffic assignment problem, genetic algorithm has been adopted for its solution. To ensue efficiency of the algorithm, the genetic operators such as crossover and mutation were designed specifically, as expressed by Equation 11, 12 and 13, so that constrains expressed by Equation 5 can be satisfied. With a test road network as an example, as shown in Figure 1, the new genetic algorithm has been proved to be very effective.
  • Keywords
    genetic algorithms; nonlinear programming; road traffic; crossover operator; genetic algorithm; multiclass traffic assignment problem; mutation operator; nonlinear optimization algorithm; nonmonotonic cost operator; static traffic assignment problem; user equilibrium; Helium; Jacobian matrices; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-7705-0
  • Type

    conf

  • DOI
    10.1109/CINC.2010.5643746
  • Filename
    5643746