A path-based algorithm is developed for the static traffic assignment problem (TAP). In each iteration, it decomposes the problem into origin-destination (OD) pairs and solves each subproblem separately using the Wolfe reduced gradient (RG) method. This method reduces the dimensions of each single-OD subproblem by selecting a basic path between the OD pair and reformulating the subproblem in terms of the nonbasic paths. A column generation technique is included to avoid path enumeration in large scale networks. Also, some speed-up techniques are designed to improve the computational efficiency. The algorithm shifts flows from costlier paths to cheaper paths; however, the amount of flow shifted from a costlier path is proportional to not only the travel time but also the flow on the path. It is applied to the Philadelphia and Chicago test problems, while different strategies for choosing the basic paths are examined. The RG algorithm shows an excellent convergence to relative gaps of the order of 1.0E-14 when compared against several reference TAP algorithms.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Reduced gradient algorithm for user equilibrium traffic assignment problem


    Contributors:

    Published in:

    Publication date :

    2020-01-01


    Size :

    25 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown