A Partial Linearization Method for the Traffic Assignment Problem

This paper presents a new solution technique for the traffic assignment problem. The approach is based on an iteratively improved nonlinear and separable approximation of the originally nonseparable objective function, and resembles the Frank-Wolfe algorithm in the sense that the subproblem separates with respect to commodities. Since the singlecommodity subproblems are strictly convex, the new algorithm will not suffer from the poor convergence behaviour of the Frank-Wolfe algorithm, which is a consequence of the extreme solutions of its linear subproblems. The solution method is outlined along with convergence results, and a dual approach to the solution of the strictly convex subproblems is described. The performance of the algorithm is illustrated with two numerical examples.