A novel flow update policy in solving traffic assignment problems: Successive over relaxation iteration method

Honggang Zhang, Zhiyuan Liu, Jian Wang and Yunchi Wu

Transportation Research Part E: Logistics and Transportation Review, 2023, vol. 174, issue C

Abstract: This paper presents a novel flow update policy, namely the successive over relaxation (SOR) iteration method, which can be implemented in traffic assignment algorithms. Most existing solution algorithms for the user equilibrium traffic assignment problem (UE-TAP) mainly use two flow update policies: Jacobi and Gauss-Seidel iteration methods. The proposed flow update policy SOR can be a more efficient replacement. Following the path-based gradient projection (GP) algorithm, we developed a new method GP-SOR for the UE-TAP. This study first provides the complete procedure of applying the GP-SOR algorithm to solve the UE-TAP. Subsequently, a few properties of the proposed method are rigorously proven. However, empirical tests of the GP-SOR algorithm demonstrate serious oscillations and poor convergence. To cope with this problem, the Armijo Rule is employed to determine the relaxation factor, which substantially improves the convergence of GP-SOR algorithm. The preliminary numerical examples show that the GP-SOR algorithm has speedier convergence compared with the known alternatives, which is reflected by the evident reduction of the computing time and the number of iterations.

Keywords: User equilibrium; Successive over relaxation iteration method; Gradient projection algorithm (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.tre.2023.103111

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