Two new mixed‐integer programming models for the integrated train formation and shipment path optimization problem

Railcars are known as the heart of the freight rail transportation industry. Hence, any improvements in their operations can lead to sharp reductions in various operating costs. One of the most critical operations on railcars is blocking and routing their transportation. Railway companies face conti...

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Published in:Networks Vol. 81; no. 3; pp. 359 - 377
Main Authors: Arsalani, Pouria, Reisi‐Nafchi, Mohammad, Dardashti, Vahid, Moslehi, Ghasem
Format: Journal Article
Language:English
Published: Hoboken, USA John Wiley & Sons, Inc 01.04.2023
Wiley Subscription Services, Inc
Subjects:
Freight railways
Integer programming
Linear programming
mixed‐integer linear programming
Operating costs
Optimization
Rail transportation
railcar blocking
Railcars
Railroad cars
Railway tracks
railway transportation
Route planning
shipment path routing
Shipments
single‐block train
train formation
Trains
Transportation industry
ISSN:0028-3045, 1097-0037
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Abstract Railcars are known as the heart of the freight rail transportation industry. Hence, any improvements in their operations can lead to sharp reductions in various operating costs. One of the most critical operations on railcars is blocking and routing their transportation. Railway companies face continuous challenged about what blocks should be formed to carry shipments across different origin–destination pairs (O–D pairs) and reclassify them in intermediate yards to minimize transportation reclassification costs. In addition, it is necessary to determine train service between O–D pairs and the number of trains. Along with the shipment routing plans, this problem is called train formation and shipment path optimization (TFSP). In TFSP, some substructure and rail network operational constraints should be considered, including link capacity, classification capacity, the number of sorting tracks, and path length. This paper presents two arc‐based mixed‐integer linear programming (MILP) models to formulate the TFSP problem. To the best of the authors' knowledge, no MILP arc‐based model has been published for the problem that does not need any preprocess before solving. Computational results of solving models on the datasets showed that the first model could obtain a feasible solution with a maximum 0.05% gap up to 48 yards instance. The second model also could find a solution with a small gap compared to the optimal solution in a reasonable time for instances up to 128 yards. Also, the proposed models were compared to the best methods in the literature, and their superiority was shown.
AbstractList Railcars are known as the heart of the freight rail transportation industry. Hence, any improvements in their operations can lead to sharp reductions in various operating costs. One of the most critical operations on railcars is blocking and routing their transportation. Railway companies face continuous challenged about what blocks should be formed to carry shipments across different origin–destination pairs (O–D pairs) and reclassify them in intermediate yards to minimize transportation reclassification costs. In addition, it is necessary to determine train service between O–D pairs and the number of trains. Along with the shipment routing plans, this problem is called train formation and shipment path optimization (TFSP). In TFSP, some substructure and rail network operational constraints should be considered, including link capacity, classification capacity, the number of sorting tracks, and path length. This paper presents two arc‐based mixed‐integer linear programming (MILP) models to formulate the TFSP problem. To the best of the authors' knowledge, no MILP arc‐based model has been published for the problem that does not need any preprocess before solving. Computational results of solving models on the datasets showed that the first model could obtain a feasible solution with a maximum 0.05% gap up to 48 yards instance. The second model also could find a solution with a small gap compared to the optimal solution in a reasonable time for instances up to 128 yards. Also, the proposed models were compared to the best methods in the literature, and their superiority was shown.
Author Moslehi, Ghasem
Dardashti, Vahid
Reisi‐Nafchi, Mohammad
Arsalani, Pouria
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SubjectTerms Freight railways
Integer programming
Linear programming
mixed‐integer linear programming
Operating costs
Optimization
Rail transportation
railcar blocking
Railcars
Railroad cars
Railway tracks
railway transportation
Route planning
shipment path routing
Shipments
single‐block train
train formation
Trains
Transportation industry
Title Two new mixed‐integer programming models for the integrated train formation and shipment path optimization problem
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