A Comparison of Optimization Methods for Solving the Depot Matching and Parking Problem

We consider the Train Unit Shunting Problem, an important plan- ning problem for passenger railway operators. This problem entails assigning physical train units to scheduled train services in such a way that the resulting shunting yard operations are feasible. As such, it arises at every shunting yard in the railway network and involves matching train units to arriving and departing train services as well as assigning the selected matchings to appropriate shunting yard tracks. We present a comparison benchmark of multiple solution approaches for this problem. In particular, we have developed a Constraint Pro- gramming formulation, a Column Generation approach, and a random- ized greedy heuristic. We compare and benchmark these approaches against slightly adjusted existing methods based on a a Mixed Inte- ger Linear Program, and a Two-Stage heuristic. The benchmark con- tains multiple real-life instances provided by the Danish State Rail- ways (DSB) and Netherlands Railways (NS). The results highlight the strengths and weaknesses of the considered approaches

A Comparison of Two Exact Methods for Passenger Railway Rolling Stock (Re)Scheduling

The assignment of rolling stock units to timetable services in passenger railways is an important optimization problem that has been addressed by many papers in different forms. Solution approaches have been proposed for different planning phases: strategic, tactical, and also operational planning. In this paper we compare two approaches within two operational planning phases (i.e. the daily and the real time planning). The first exact approach is based on a Mixed Integer Linear Program (MILP) which is solved using CPLEX. The second approach is an extension of a recently introduced column generation approach. In this paper, we benchmark the performance of the methods on networks of two countries (Denmark and The Netherlands). We use the approaches to make daily schedules and we test their real time applicability by performing tests with different disruption scenarios. The computational experiments demonstrate that both models can be used on both networks and are able to find optimal rolling stock circulations in the different planning phase