Optimisation du personnel ferroviaire : une approche matheuristique

Nicolas Zufferey, professeur à la GSEM, a co-écrit un article avec Marie-Sklaerder Vié et Stefan Minner publié dans la revue de premier plan OR Spectrum. L'étude aborde le problème de l’ordonnancement des locomotives et des conducteurs auquel est confrontée SBB Cargo AG. La coordination efficace des trains et des conducteurs est essentielle pour optimiser les opérations et réduire les coûts. Leur approche innovante combine des méthodes d'optimisation mathématique avec des heuristiques, ce qui résulte en une matheuristique. Cette méthode hybride permet de trouver un équilibre entre l'efficacité computationnelle et la qualité des solutions.

Nicolas Zufferey a bénéficié du soutien de CFF Cargo AG et de l'Université de Genève.

ABSTRACT

At the scale of Switzerland, the national railway company SBB Cargo AG has to schedule its locomotives and drivers in order to be able to pull all trains. Two objective functions are considered in a two-stage lexicographic fashion: (1) the locomotive and driver costs and (2) the driver time that is spent without driving. As the problem instances tend to reach big sizes (up to 1900 trains), we propose to schedule locomotives and drivers in a sequential way, thus having a sequence of smaller problems to solve. Moreover, for smaller instances, we also propose to schedule jointly locomotives and drivers in an integrated way, therefore increasing the search space but possibly leading to better solutions. In this paper, we present a mathematical formulation and model for the problem. We also consider the contract-related constraints of the drivers, and we propose a way to integrate some time flexibility in the schedules. Next, we propose an innovative matheuristic to solve the problem, relying on a descent local search and a rolling horizon decomposition. An important goal of this method is to explore thoroughly at which extent a general-purpose solver can be used on this problem. Finally, the benefits of each aspect of the model and of the method are analyzed in detail on the results obtained for 20 real SBB Cargo AG instances.

Accédez à l'étude : A matheuristic for tactical locomotive and driver scheduling for the Swiss national railway company SBB Cargo AG (en anglais)

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20 février 2024