Traffic network optimization aims to improve a given road network by maximizing the utility for traffic participants. The present thesis investigates a solution-based approach for tackling the traffic network optimization problem by modifying an established metaheuristic - the genetic algorithm - in such a way that mutation does not appear at random but with the help of a local optimization procedure. In comparison to the standard genetic algorithm, the approach using local optimization in form of a neighbourhood search should result in increased solutions. Primarily, we have to make a statement regarding how well a network performs with respect to traffic participants. One opportunity might be to approximate the utility based on the travel time of road users. This evaluation forms the basis of the neighbourhood search. Finally, by means of practical data we compare and assess the aforementioned enhanced approach with the standard genetic algorithm in terms of quality and development.     «

Traffic network optimization aims to improve a given road network by maximizing the utility for traffic participants. The present thesis investigates a solution-based approach for tackling the traffic network optimization problem by modifying an established metaheuristic - the genetic algorithm - in such a way that mutation does not appear at random but with the help of a local optimization procedure. In comparison to the standard genetic algorithm, the approach using local optimization in form...     »