Title :
Solving multi-class traffic assignment problem with genetic algorithm
Author :
Zhang, Guoqiang ; Chen, Jun
Author_Institution :
Transp. Coll., Southeast Univ., Nanjing, China
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;
Conference_Titel :
Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7705-0
DOI :
10.1109/CINC.2010.5643746