In continuation of a set of types of problems in fleet management science, Rail and inter-modal transportation have several noteworthy approaches to solutions.

Rail and inter-modal is a complex system composed by different transport networks, infrastructures, different transport means and operators, such as dryage operators, terminal operators, network operators and others. Intermodal means there are lots of decision makers who must work in a coordinated manner for the system to run smoothly. If intermodal transport is to be developed, it will require more decision-making support tools to assist the decision-makers and stakeholders.

When train operations are perturbed, a new conflict free timetable must be recomputed such that the deviation from the original must be minimized. This scheduling problem is modeled with an alternative graph formulation and a branch and bound algorithm is developed. Some approaches use an integrated framework which deals with signal layout optimization, train scheduling optimization at microscopic level, and others.

Heuristic approaches include a look-ahead greedy heuristic and a global neighborhood search algorithm, in terms of railway total train delay. Scheduling additional train services to be integrated into the current timetables is a problem that is modeled as a hybrid job shop scheduling techniques that operate upon a disjunctive graph model of trains.

One approach d              evelops a train slot selection model based on multicommodity network flow concepts for determining freight train timetables. This helps to schedule rail services along multiple interconnected routes. This model seeks to minimize operating costs incurred by the carriers and delays incurred by the shippers. The schedules and demand levels are ensured to be mutually consistent. When the model is embedded in a simulation, it can be used iteratively and together with the output of the scheduling solution.

Another approach solves the freight transportation on hybrid rail networks used to transport both passengers and freight. It uses a preferred timetable as input for each freight train. Some overrides are permitted such as specifying a path different from the one in the ideal timetable. It’s objective is to introduce as many new freight trains as possible by assigning them timetables that are as close as possible to the ideal ones. An integer linear programming method is used in the model.

A third approach specifically takes into account the double-track train scheduling. It focuses on the high-speed passenger rail line in an existing network and minimizes both the expected wait times for high speed trains and the total travel times of both speed trains. Using the priority for speed, the problem is translated as multi-mode resource project. It is then solved for scheduling with a branch and bound algorithm and a beam search algorithm.

The autonomous fleet management differs from these in that the destinations must be determined. If the dependencies can be expressed in quadratic form, then the steepest gradient method can point to the optimum destination.