We can encounter railway freight car optimization problems in all aspects of railroad life. They can be classified according to their main task into several sub-problems, e.g., fleet management, freight car distribution, time-tabling, crew scheduling, and shunting. In this thesis we consider a shunting problem in marshalling yards which turns out to be MP-hard. Thus, it seems unlikely to compute efficiently an optimal solution for large-scale instances. This motivates the search for fast algorithms providing upper and lower bounds on the optimal solution with provable and admissible performance guarantee. On the other hand, we model a network with a directed and weighted graph and propose an algorithmic approach for the empty freight car distribution problem. We have a closer look on a particular issue of this real-word problem which turns out to be a generalized network flow problem. In the Train Marshalling Problem we deal with the task to rearrange an incoming sequence of freight cars in a shunting yard, such that cars of the same destinations are blocked together in the final train, while minimizing the number of necessary classification tracks. Furthermore, we allow one roll-in operation for every car and one pull-out operation per track. We consider the problem of distributing empty freight cars in a scheduled railway system. We describe the main components of the current planing process and present an initial network flow model and an algorithmic approach for determining a freight car distribution with minimal total costs of transportation. Since the reality requires much more adaptions and features of the distribution process, we describe some requirements more detailed and propose approaches to deal with them. Thereby, we focus on a reoptimization procedure which deals with changes occured in the input data set. In the generalized maximum flow problem, the aim is to find a maximum flow in a generalized network, i.e., a network with multipliers on the arcs that specify which portion of the flow entering an arc at its tail node reaches its head node.
On the solution of some railway freight car optimization problems
Mathematik ; 1-172
2011
172 Seiten, Bilder, Tabellen, 65 Quellen
Hochschulschrift
Englisch
Optimization of Railway Freight Shunting
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