Railway crew scheduling with semi-flexible timetables
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Railway crew scheduling with semi‑flexible timetables Christian Rählmann1 · Ulrich W. Thonemann1 Received: 22 June 2019 / Accepted: 15 May 2020 © The Author(s) 2020
Abstract We investigate the impact of coordinating the timetable and the crew schedule in an operational freight railway system. Usually, those problems are solved sequen‑ tially—resulting in suboptimal schedules for train drivers due to large idle times between two train rides. We seek to coordinate the timetable and the crew schedule on the operational level by adding flexibility to the timetable. We introduce small time windows that allow to shift entire trains forwards and backwards by discrete time periods. We present a mathematical model and solve it with a column genera‑ tion heuristic. We test our model on three real datasets of a major European Freight Railway Operator and show that significant reduction in idle time and cost can be achieved. Keywords Scheduling · Railway crew scheduling · Timetable · Transportation
1 Introduction Freight railway operators must coordinate their resources (track capacity, engines and train drivers) to transport their customers’ goods. Typically, the companies split their resource planning process into three phases (Kroon et al. 2009; Huisman et al. 2005b; Lusby et al. 2011): timetabling, engine scheduling and crew sched‑ uling. In timetabling, the arrival and departure times of the trains are determined based upon the track availability. In engine scheduling, engines are assigned to each train. Finally in crew scheduling, different tasks are combined to duties into a crew schedule. The companies solve these phases separately due to the complexity of the large rail‑ way networks. However, the integration of these problems will most likely free great potential because it can coordinate the resources simultaneously and therefore use them more efficiently. The full integration of the three phases for practical problem sizes * Christian Rählmann christian.raehlmann@uni‑koeln.de 1
Department of Supply Chain Management and Management Science, University of Cologne, 50923 Cologne, Germany
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seems not feasible at the moment. Research focuses on integrating adjacent phases of the planning process, that is, integrating the timetabling with the engine scheduling (e.g. Bach et al. 2015; Schmid and Ehmke 2015) or integrating the engine scheduling with the crew scheduling (e.g. Kliewer et al. 2012). These approaches cannot address one of the main problems in crew scheduling, low productivity of duties, that is, long idle time of train drivers when switching trains (see Jütte and Thonemann 2015 for a detailed analysis for waiting time per trip connection). At a major European Freight Railway Operator (EFRO), who initiated our research, train drivers frequently wait at train stations in order to drive the next train back to their home depot. These long waiting times can be attributed to the underlying timetables and not to the engine schedule, such that these canno
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