A hybrid genetic algorithm for road congestion minimization

One of the main goals in a transportation planning process is to achieve solutions for two classical problems: the traffic assignment problem, which minimizes the total travel delay among all travelers, and the toll pricing problem which settles, based on data derived from the first problem, the tolls that would collectively benefit all travelers and would lead to a user equilibrium solution. Acquiring precision for this framework is a challenge for large networks. In this article, we propose an approach to solve the two problems jointly, making use of a Hybrid Genetic Algorithm for the optimization of transportation network performance by strategically allocating tolls on some of the links. Since a regular transportation network may have thousands of intersections and hundreds of roads, our algorithm takes advantage of mechanisms for speeding up shortest path algorithms.