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

Abstract

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.