SAPI: Statistical Analysis of Propagation of Incidents. A new approach for rescheduling trains after disruptions |
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Authors: | Rodrigo Acuna-Agost Philippe MichelonDominique Feillet Serigne Gueye |
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Institution: | a Université d’Avignon et des Pays de Vaucluse, Laboratoire Informatique d’Avignon, F-84911 Avignon, France b Amadeus SAS, Operations Research and Innovation Division, F-06902 Sophia Antipolis, France c École des Mines de Saint-Étienne, CMP Georges Charpak, F-13541 Gardanne, France d Université du Havre, Laboratoire de Mathématiques Appliquées du Havre, F-76058 Le Havre, France |
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Abstract: | In this paper, we present a new approach to solve the railway rescheduling problem. This problem deals with the reparation of a disturbed railway timetable after incidents in such a way to minimize the difference between the original plan and the new provisional plan. We use a mixed integer linear programming (MIP) formulation that models this problem correctly. However, the large number of variables and constraints denies the possibility to solve this problem efficiently using a standard MIP solver. A new approach called SAPI (Statistical Analysis of Propagation of Incidents) has been developed to tackle the problem. The key point of SAPI is to estimate the probability that an event, one step of the itinerary of a train, is affected by a set of incidents. Using these probabilities, the search space is reduced, obtaining very good solutions in a short time. The method has been tested with two different networks located in France and Chile. The numerical results show that our procedure is viable in practice. |
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Keywords: | Timetabling Transportation Integer programming Logistic regression Disruption management Railways |
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