In intermodal transport multiple types of vehicles are used to transport containers. If the routes of the vehicles are known, then the container allocation can be optimized. This problem can be modelled as an integral multi-commodity min cost flow problem on a time-space graph. This model has an arc-based and path-based form. In this thesis, the path-based form is derived from the arc-based form. Some of the methods that can be used to solve this model are column generation, Lagrangian relaxation and the repeated cheapest path heuristic.
If the routes of the vehicles are not known, then we also need to create routes for the vehicles. The problem of routing vehicles and scheduling containers can be modelled as a multi-commodity network design problem on a time-space graph. Variable reductions, cutting planes and other additional constraints are looked into to make the problem easier to solve. Additions to the model are researched that can make the model more suitable for use in practice. Additionally, ILP based solution methods are developed. Finally, some of these
reductions, extensions and solution methods are implemented and reviewed.