Timetable rearrangement to cope with railway maintenance activities

• Published in: Computers & operations research 2018-07, Vol.95, p.123-138
• Main Authors: Arenas, Diego, Pellegrini, Paola, Hanafi, Saïd, Rodriguez, Joaquin
• Format: Article
• Language: English
• Subjects: Infrastructure; Integer programming; Linear programming; Maintenance; Mathematics; MILP; Operations research; Optimization and Control; Rail transportation; Railroads; Railway maintenance; Reliability; Repair & maintenance; Rolling stock; Stormwater; Studies; Temporary speed limitations; Timetables; Train timetabling; Trains
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2018.02.018

•We introduce RECIFE-MAINT, a MILP formulation to solve the problem of rearranging a timetable to cope with railway infrastructure maintenance.•RECIFE-MAINT considers specific aspects of maintenance such as maintenance trains and temporary speed limitations.•We propose two algorithms to solve RECIFE-MAINT which are tested in a real scenario of the French railway network.•Our solution approaches obtain considerably better solutions than the algorithm emulating the current practice.•We identify and analyse some characteristics of the instances of the problem having an impact on their difficulty. Maintenance activities on the railway infrastructure are necessary to maintain its functionality and availability. Commonly, the maintenance activities are planned first. Then, the timetable is elaborated respecting the unavailability periods caused by the former. However, sometimes unplanned maintenance activities have to be introduced at short notice, and the timetable must be rearranged to respect the new unavailabilities. In addition, specific trains may be necessary to perform maintenance activities, and they are typically not scheduled in the timetable. In this case, the timetable may need to be further rearranged to integrate the maintenance trains. In this paper, we propose a mixed-integer linear programming formulation that rearranges a timetable to cope with the capacity consumption produced by maintenance activities. It includes the consideration of maintenance trains and other specific constraints, such as temporary speed limitations. In this formulation, the rearrangement of the timetable is optimized based on a microscopic representation of both the infrastructure and the rolling stock. We assess three algorithms founded on this formulation on a real case study in the French railway network and we show their practical applicability.