A graph vertex-coloring-based parallel block coordinate descent method for solving the traffic assignment problem

•OD pair partitioning is formulated as a vertex-coloring-based integer linear programming (ILP) problem.•A largest degree first algorithm solves the ILP problem to minimize OD path overlap within each block.•The vertex-coloring-based OD partitioning result is used as input for parallel traffic assig...

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Vydáno v:Transportation research. Part C, Emerging technologies Ročník 183; s. 105439
Hlavní autoři: Zhang, Kai, Liu, Zhiyuan, Zhang, Honggang, Zhang, Yicheng, Tang, Yuk Ming, Fu, Xiaowen
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.02.2026
Témata:
Integer Linear Programming
Parallel Block Coordinate Descent Method
Traffic Assignment
Vertex-coloring
Parallel Block Coordinate Descent Method
Vertex-coloring
Integer Linear Programming
Traffic Assignment
ISSN:0968-090X
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Shrnutí:•OD pair partitioning is formulated as a vertex-coloring-based integer linear programming (ILP) problem.•A largest degree first algorithm solves the ILP problem to minimize OD path overlap within each block.•The vertex-coloring-based OD partitioning result is used as input for parallel traffic assignment algorithm.•An adaptive algorithm solves the OD-based TAP based on OD path numbers.•Validated on five transport networks, showing significant efficiency gains for large-scale TAPs. Traffic assignment is an essential component of the traditional four-step transportation planning methodology and significantly contributes to the prediction of traffic flow distribution and optimization of traffic planning. Existing algorithms for solving the user equilibrium traffic assignment problem typically rely on equal intervals and random sampling strategies to divide a set of origin–destination (OD) pairs. However, these sampling strategies fail to address the path overlap issue among OD pairs and often depend on sensitivity analyses to partition the OD set, hindering the efficiency of task parallelism. To address this challenge, the OD grouping problem was formulated as a vertex-coloring problem, which was translated into an integer linear programming (ILP) model. The largest degree first algorithm was proposed to solve the OD grouping problem, enabling the identification of OD pairs within each block with minimal path overlap. Thereafter, the results of the OD grouping based on vertex coloring were incorporated into the parallel block coordinate descent (PBCD) method, increasing the number of OD subproblems within each block and enhancing the parallel computation. An adaptive algorithm is further proposed to address the OD-based restricted subproblem depending on the number of paths for a given OD pair. The proposed method is evaluated based on various large-scale transportation networks and compared with existing algorithms, demonstrating its effectiveness in reducing path overlap within blocks and improving the efficiency of solving traffic assignment problems in large-scale networks.
ISSN:0968-090X
DOI:10.1016/j.trc.2025.105439