Primal Method for Determining the Most Likely Route Flows in Large Road Networks
Transportation Science
Second Derivative Approximation for Origin-Based Algorithm
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
Algorithms for distributing traffic flows
Automation and Remote Control
Using ACCPM in a simplicial decomposition algorithm for the traffic assignment problem
Computational Optimization and Applications
A comparison of feasible direction methods for the stochastic transportation problem
Computational Optimization and Applications
A Note on Bar-Gera's Algorithm for the Origin-Based Traffic Assignment Problem
Transportation Science
Finding flow equilibrium with projective methods with decomposition and route generation
Automation and Remote Control
An efficient solution algorithm for solving multi-class reliability-based traffic assignment problem
Mathematical and Computer Modelling: An International Journal
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We present an origin-based algorithm for the traffic assignment problem, which is similar conceptually to the algorithm proposed by Gallager and Bertsekas for routing in telecommunication networks. Apart from being origin-based, the algorithm is different from other algorithms used so far for the traffic assignment problem by its restriction to acyclic solutions and by the use of approach proportions as solution variables. Projected quasi-Newton search directions are used to shift flows effectively and to eliminate residual flows. Experimental results comparing the proposed algorithm with the state-of-the-practice algorithm of Frankand Wolfe demonstrate the algorithm's excellent convergence performance, especially when highly accurate solutions are needed. Reasonable memory requirements make this algorithm applicable to large-scale networks. The resulting solution has an immediate route flow interpretation, thus providing equivalent detail to route-based solutions.