A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport

In this work, we consider the integrated problem of locomotive scheduling and driver assignment in rail freight companies. Our aim is to compute an optimal simultaneous assignment of locomotives and drivers to the trains listed in a given order-book. Mathematically, this leads to the combination of...

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Main Authors: Andreas Bärmann, Alexander Martin, Jonasz Staszek
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:EURO Journal on Transportation and Logistics
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Online Access:http://www.sciencedirect.com/science/article/pii/S2192437624000207
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author Andreas Bärmann
Alexander Martin
Jonasz Staszek
author_facet Andreas Bärmann
Alexander Martin
Jonasz Staszek
author_sort Andreas Bärmann
collection DOAJ
description In this work, we consider the integrated problem of locomotive scheduling and driver assignment in rail freight companies. Our aim is to compute an optimal simultaneous assignment of locomotives and drivers to the trains listed in a given order-book. Mathematically, this leads to the combination of a set-packing problem with compatibility constraints and a multi-commodity-flow problem. We develop a binary-programming formulation to model the given task and improve it by performing a clique-based tightening of the original set-packing inequalities. The objective function of this model makes sure that as many trains as possible are running. To handle the computational complexity of the problem, we introduce a novel decomposition approach which decomposes the problem into a master locomotive scheduling problem and a subproblem for driver assignment. It exploits the fact that the master problem is empirically much easier to solve than the subproblem. For any fixed solution of the master problem, we can use the subproblem to either confirm feasibility of the master solution or to derive valid inequalities from various constraint classes to cut the infeasible master solution off and reiterate. To further improve solution times, we also develop a presolve heuristic. We demonstrate the potential of the presented method by solving a large-scale real-world problem instance provided by our industry partner DB Cargo Polska S.A., as well as a set of derived realistic instances.
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spelling doaj-art-e35e8d1f7a204023aecef9dd0b9616642025-08-20T01:55:40ZengElsevierEURO Journal on Transportation and Logistics2192-43842024-01-011310014510.1016/j.ejtl.2024.100145A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transportAndreas Bärmann0Alexander Martin1Jonasz Staszek2Lehrstuhl für Analytics & Mixed-Integer Optimization, Department of Data Science/Department Mathematik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstraße 11, 91058 Erlangen, GermanyAnalytics and Optimization Lab, Technische Universität Nürnberg, Ulmenstr. 52, 90544 Nürnberg, GermanyAnalytics and Optimization Lab, Technische Universität Nürnberg, Ulmenstr. 52, 90544 Nürnberg, Germany; Corresponding author.In this work, we consider the integrated problem of locomotive scheduling and driver assignment in rail freight companies. Our aim is to compute an optimal simultaneous assignment of locomotives and drivers to the trains listed in a given order-book. Mathematically, this leads to the combination of a set-packing problem with compatibility constraints and a multi-commodity-flow problem. We develop a binary-programming formulation to model the given task and improve it by performing a clique-based tightening of the original set-packing inequalities. The objective function of this model makes sure that as many trains as possible are running. To handle the computational complexity of the problem, we introduce a novel decomposition approach which decomposes the problem into a master locomotive scheduling problem and a subproblem for driver assignment. It exploits the fact that the master problem is empirically much easier to solve than the subproblem. For any fixed solution of the master problem, we can use the subproblem to either confirm feasibility of the master solution or to derive valid inequalities from various constraint classes to cut the infeasible master solution off and reiterate. To further improve solution times, we also develop a presolve heuristic. We demonstrate the potential of the presented method by solving a large-scale real-world problem instance provided by our industry partner DB Cargo Polska S.A., as well as a set of derived realistic instances.http://www.sciencedirect.com/science/article/pii/S2192437624000207Integrated locomotive scheduling and driver assignmentRailway transportInteger programmingDecompositionCutting planes
spellingShingle Andreas Bärmann
Alexander Martin
Jonasz Staszek
A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport
EURO Journal on Transportation and Logistics
Integrated locomotive scheduling and driver assignment
Railway transport
Integer programming
Decomposition
Cutting planes
title A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport
title_full A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport
title_fullStr A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport
title_full_unstemmed A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport
title_short A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport
title_sort decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport
topic Integrated locomotive scheduling and driver assignment
Railway transport
Integer programming
Decomposition
Cutting planes
url http://www.sciencedirect.com/science/article/pii/S2192437624000207
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