Bilevel O/D Matrix Adjustment Formulation Using High Convergence Assignment Methods

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 262)


The Frank-Wolfe algorithm has been for years the most widely used method for solving the traffic assignment problem (TAP). In the last decade there have been new proposals for the resolution of the TAP. It has been shown that these algorithms are feasible for large scale problems with very high convergence, much higher than the achieved by the Frank-Wolfe algorithm. The O/D matrix adjustment problem based upon traffic counts can be formulated as a bilevel optimization problem in which the TAP is the lower level. The convergence of the TAP and the computational cost can be critical because the number of TAPs to be solved during each step of the process is very high. This paper exploits the possibilities offered by new TAP methods in the O/D matrix adjustment problem. Numerical examples on medium-sized networks using the new proposed methods are presented.


O/D matrix adjustment Traffic assignment problem Origin based algorithm 



This research was funded in part by both the Spanish Ministry of Science (National Plan Programs TRA2012-36930, FPI BES-2009-025110) and the Spanish Ministry of Public Works (P63/08). One of the authors, L.M. Romero, acknowledges the support of the grant PTQ-11-04952 from the Spanish Ministry of Science through the INNCORPORA-PTQ Programme.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Transportation EngineeringUniversity of SevillaSevillaSpain
  2. 2.Transportation EngineeringAICIASevillaSpain

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