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Economies of Scale in Empty Freight Car Distribution in Scheduled Railways

Author

Listed:
  • Martin Joborn

    (Carmen Consulting, Maria Bangata 6, SE-118 63, Stockholm, Sweden)

  • Teodor Gabriel Crainic

    (Intelligent Transportation Systems Laboratory, Centre de recherche sur les transports, Université de Montréal, C.P. 8888, Succursale Centre-ville, Montréal, Québec, Canada H3C 3J7, and Département de management et technologie, École des Sciences de la Gestion, Université du Québec à Montréal, C.P. 6192, Succursale Centre-ville, Montréal, Québec, Canada H3C 4R2)

  • Michel Gendreau

    (Centre de recherche sur les transports, and Département d'informatique et de recherche opérationnelle, Université de Montréal, Montréal, Québec, Canada H3C 3J7)

  • Kaj Holmberg

    (Department of Mathematics, Linköping Institute of Technology, Linköping University, SE-581 83 Linköping, Sweden)

  • Jan T. Lundgren

    (Department of Science and Technology, Campus Norrköping, Linköping University, SE-601 74 Norrköping, Sweden)

Abstract

In this paper, we consider empty freight car distribution in a scheduled railway system. We analyze the cost structure for the repositioning of empty cars, and conclude that the distribution cost shows an economy-of-scale behavior. In addition to the cost proportional to the number of cars sent from origin to destination, there is a cost related to car-handling operations at yards, which depends on the number of car groups that are handled. Thus, if we can find a transportation pattern in which fewer but larger groups of cars are built, the total distribution cost can be decreased.The objective of the paper is to propose an optimization model that explicitly takes this economy-of-scale effect into account. We use a time-dependent network to describe the possible car movements in time and space, and show how this network can be transformed into a network with fixed costs on links representing movements of cars with identical origin and destination terminals. The resulting optimization model is a capacitated network design model, where each capacity constraint limits the flow on several arcs. We describe a tabu heuristic for solving the model, and present computational results.

Suggested Citation

  • Martin Joborn & Teodor Gabriel Crainic & Michel Gendreau & Kaj Holmberg & Jan T. Lundgren, 2004. "Economies of Scale in Empty Freight Car Distribution in Scheduled Railways," Transportation Science, INFORMS, vol. 38(2), pages 121-134, May.
  • Handle: RePEc:inm:ortrsc:v:38:y:2004:i:2:p:121-134
    DOI: 10.1287/trsc.1030.0061
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    References listed on IDEAS

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    Cited by:

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    3. Belgacem Bouzaiene-Ayari & Clark Cheng & Sourav Das & Ricardo Fiorillo & Warren B. Powell, 2016. "From Single Commodity to Multiattribute Models for Locomotive Optimization: A Comparison of Optimal Integer Programming and Approximate Dynamic Programming," Transportation Science, INFORMS, vol. 50(2), pages 366-389, May.
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    5. G Lulli & U Pietropaoli & N Ricciardi, 2011. "Service network design for freight railway transportation: the Italian case," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2107-2119, December.
    6. Behrens, Kristian & Picard, Pierre M., 2011. "Transportation, freight rates, and economic geography," Journal of International Economics, Elsevier, vol. 85(2), pages 280-291.
    7. Milos Milenkovic & Nebojsa Bojovic, 2014. "Fuzzy modeling approach to the rail freight car inventory problem," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(2), pages 119-137, March.
    8. Sangpil Ko & Pasi Lautala & Kuilin Zhang, 2020. "Data-Driven Study on the Sustainable Log Movements: Impact of Rail Car Fleet Size on Freight Storage and Car Idling," Sustainability, MDPI, vol. 12(11), pages 1-15, June.
    9. Schwerdfeger, Stefan & Otto, Alena & Boysen, Nils, 2021. "Rail platooning: Scheduling trains along a rail corridor with rapid-shunting facilities," European Journal of Operational Research, Elsevier, vol. 294(2), pages 760-778.
    10. Zu, Yue & Heydari, Ruhollah & Chahar, Kiran & Pranoto, Yudi & Cheng, Clark, 2022. "A railcar re-blocking strategy via Mixed Integer Quadratic Programming," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).
    11. Wennan Song & Di Liu & Wenyu Rong, 2022. "Optimization of Passenger-like Container Train Running Plan Considering Empty Container Dispatch," Sustainability, MDPI, vol. 14(8), pages 1-23, April.
    12. Teodor Gabriel Crainic & Nicoletta Ricciardi & Giovanni Storchi, 2009. "Models for Evaluating and Planning City Logistics Systems," Transportation Science, INFORMS, vol. 43(4), pages 432-454, November.
    13. Holmberg, Kaj & Joborn, Martin & Melin, Kennet, 2008. "Lagrangian based heuristics for the multicommodity network flow problem with fixed costs on paths," European Journal of Operational Research, Elsevier, vol. 188(1), pages 101-108, July.
    14. Zhuzhu Song & Wansheng Tang & Ruiqing Zhao, 2022. "Implications of economies of scale and scope for round-trip shipping canvassing with empty container repositioning," Annals of Operations Research, Springer, vol. 309(2), pages 485-515, February.
    15. Lawley, Mark & Parmeshwaran, Vijay & Richard, Jean-Philippe & Turkcan, Ayten & Dalal, Malay & Ramcharan, David, 2008. "A time-space scheduling model for optimizing recurring bulk railcar deliveries," Transportation Research Part B: Methodological, Elsevier, vol. 42(5), pages 438-454, June.
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    17. Amar Kumar Narisetty & Jean-Philippe P. Richard & David Ramcharan & Deby Murphy & Gayle Minks & Jim Fuller, 2008. "An Optimization Model for Empty Freight Car Assignment at Union Pacific Railroad," Interfaces, INFORMS, vol. 38(2), pages 89-102, April.

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