A train tracking system includes a train tracking module, a plurality of input sources providing train related information, and one or more interface(s) associated with the train tracking module, wherein the train tracking module is configured via computer executable instructions and through operation of a processor to receive the train related information from the plurality of input sources via the one or more interface(s), determine a position of a train within a train track map, the position of the train corresponding to a track location of the train in a track network, and wherein the train tracking module further comprises a learning algorithm, the train tracking module being configured to, utilizing the learning algorithm, determine an unexpected occupancy of the track location.

A method for assigning train blocks at a railroad merchandise yard includes determining, using a first optimization model and historical train block volume data, a first list of train block assignments for a plurality of train blocks and a plurality of classification tracks of a classification bowl. The method further includes displaying the first list of train block assignments generated by the first optimization model if the volume of the train blocks is not greater than the total available track length of the classification tracks. The method further includes determining and displaying, using a second optimization model and the historical train block volume data, a second list of train block assignments for the plurality of train blocks and the plurality of classification tracks of the classification bowl if the volume of the plurality of train blocks is greater than the total available track length of the plurality of classification tracks.

A method for assigning train blocks at a railroad merchandise yard includes determining, using a first optimization model and historical train block volume data, a first list of train block assignments for a plurality of train blocks and a plurality of classification tracks of a classification bowl. The method further includes displaying the first list of train block assignments generated by the first optimization model if the volume of the train blocks is not greater than the total available track length of the classification tracks. The method further includes determining and displaying, using a second optimization model and the historical train block volume data, a second list of train block assignments for the plurality of train blocks and the plurality of classification tracks of the classification bowl if the volume of the plurality of train blocks is greater than the total available track length of the plurality of classification tracks.