Summary: The tactical planning of rail freight networks is studied with the help of non-convex optimization models which are difficult to solve using only exact methods. For this reason it is necessary to use heuristic methods to obtain the solution for realistic networks. In this paper, local search and branch-and-bound methods are compared. In Part I, the model and the methods are defined and tested. In Part II, the methods are compared among one another using statistical analysis. The problem is to decide the optimal assignment of the trains to the service network and simultaneously assign the demand of cars to the routes. The formulation includes some features such as car transfer and classification, different capacities and a limited fleet of trains available for use. Different heuristics have been developed to obtain the solution for the proposed model: simulated annealing, tabu search and a particular heuristic that will be mentioned with the name of ‘Descending’. The objective function becomes piecewise linear if the investment cost to purchase trains is considered. For small size networks a reformulation of the problem is study to compare the heuristic approaches with the exact solution provided by branch-and-bound. To solve large networks, only heuristic methods can be used.