A set packing approach for scheduling passenger train drivers: the French experience

Abstract : In this paper, we describe a method to solve the passenger crew scheduling problem for SNCF (the French national railway company). From rolling-stock rosters, the primary objective of the problem we address is to build shifts to maximize the number of trains that are assigned to drivers. Other objectives are mainly concerned with limiting the number of times where drivers have to rest away from their home, and with minimizing taxi trips. The problem is solved with a day-by-day approach, while guaranteeing a consistent chaining on consecutive days for shifts which include an external rest for drivers. Each day, a set of shifts is first generated according to regulation and business rules using a depth-first search algorithm. Then an iterative procedure based on a Lagrangian heuristic is used to solve the resulting set packing model. This procedure relies on a three-step algorithm: a subgradi-ent method, a constructive heuristic and a fixation technique for selecting efficient shifts. The algorithm has been implemented in a proprietary software module: PLAISANCE. Numerical experiments have been performed on several real-life instances with up to 2,300 passenger trains to schedule. The results correspond to the business requirements and prove the effectiveness of the described method.
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Aurélien Froger, Olivier Guyon, Eric Pinson. A set packing approach for scheduling passenger train drivers: the French experience. RailTokyo2015, Mar 2015, Tokyo, Japan. ⟨hal-01138067⟩

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