Planning in Railway Logistic is an activity with growing importance. This is due to the high costs of investment to increase the railway capacity. Nevertheless, planning in this context is a cumbersome task, since a precise representation is necessary to consider most relevant points in this activity. Mathematical programming is becoming one of the best ways derive precise representations and to solve them. This is due to the recent advances on algorithms and computers used in the resolution of mathematical programming problems. This dissertation presents models and algorithms for tactical and strategical railway planning what is done by studying a demand planning problem (PPA). First, this problem is considered assuming that all the railway structure is defined: the network, the locomotives and wagons available, the yards for loading and unloading with their respective rates, and the forecast of demands. Next, the question of deciding the yards to stop is considered. Finally, in a third step, the effect of congestion in parts of the network is introduced to the models. This allows analyzing the variation in the travel times and its consequence in the logistic structure capacity. Models are presented for all cases of the PPA. Exact and heuristic algorithms, as well as pre-processing techniques, are described for the problem resolution. In all cases, the resulting approach allowed to solve the problems optimally or quasioptimally in a reasonable computing time. Computational results are presented on a wide set of real world instances.