Recoverable Robust Maintenance Location Routing for Rolling Stock



We consider the problem of locating maintenance facilities in a railway setting. Different facility sizes can be chosen for each candidate location. We have a discrete set with capacities and associated fixed facility costs, for each maintenance facility, that can capture the economies of scale. Because of the strategic nature of facility location, this problem has to be feasible for the current situation, but also for any of the scenarios that can occur in the future. These discrete scenarios capture changes such as changes to the rolling stock schedule, up and down-scaling of service frequencies and the introduction of new rolling stock types. We allow recovery in the form of opening additional facilities, closing facilities and upgrading the facility size for each scenario. We provide a two-stage robust programming formulation. In the first stage, we decide where to open what size of facility. In the second stage, we solve a NP-hard maintenance location routing problem.  We reformulate the problem as a mixed integer program that can be used to make an efficient column-and-constraint generation algorithm that improves the computational time and can handle larger instances due to more efficient memory usage. Furthermore, we perform an extensive case study with data from the Dutch Railways.

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