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.
Reduced gradient algorithm for user equilibrium traffic assignment problem
Transportmetrica A: Transport Science ; 16 , 3 ; 1111-1135
2020-01-01
25 pages
Article (Journal)
Electronic Resource
Unknown
Solving the Multiclass Percentile User Equilibrium Traffic Assignment Problem
Transportation Research Record | 2013
|Slope-Based Multipath Flow Update Algorithm for Static User Equilibrium Traffic Assignment Problem
Online Contents | 2010
|Slope-Based Multipath Flow Update Algorithm for Static User Equilibrium Traffic Assignment Problem
Transportation Research Record | 2010
|A Distributed Algorithm for the Dynamic Traffic Equilibrium Assignment Problem
British Library Conference Proceedings | 1996
|General Stochastic User Equilibrium Traffic Assignment Problem with Link Capacity Constraints
Online Contents | 2008
|