2024/06/11 by Rui Yao, Mogens Fosgerau, Mads Paulsen +1
Engineering · Social Sciences · #Traffic control and management #Transportation Planning and Optimization #Transportation and Mobility Innovations
paper · doi:10.1287/trsc.2023.0449
openalex publication_date 2024/06/11 · crossref created 2024/06/11 · crossref issued 2024/07/01 · crossref published 2024/07/01 · crossref published-print 2024/07/01 · crossref deposited 2024/08/02 · openalex created_date 2025/10/10 · crossref indexed 2026/07/31 · openalex updated_date 2026/08/01
This paper develops a fast algorithm for computing the equilibrium assignment with the perturbed utility route choice (PURC) model. Without compromise, this allows the significant advantages of the PURC model to be used in large-scale applications. We formulate the PURC equilibrium assignment problem as a convex minimization problem and find a closed-form stochastic network loading expression that allows us to formulate the Lagrangian dual of the assignment problem as an unconstrained optimization problem. To solve this dual problem, we formulate a quasi-Newton accelerated gradient descent algorithm (qN-AGD*). Our numerical evidence shows that qN-AGD* clearly outperforms a conventional primal algorithm and a plain accelerated gradient descent algorithm. qN-AGD* is fast with a runtime that scales about linearly with the problem size, indicating that solving the perturbed utility assignment problem is feasible also with very large networks. Funding: This work has been financed by the European Union—NextGenerationEU.