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The Canadian Pacific Railway Transforms Operations by Using Models to Develop Its Operating Plans

Author

Listed:
  • Phil Ireland

    (Canadian Pacific Railway, Gulf Canada Square, Suite 400, 401-9th Avenue SW, Calgary, Alberta, Canada T2P 4Z4)

  • Rod Case

    (Canadian Pacific Railway, Gulf Canada Square, Suite 400,401-9th Avenue SW, Calgary, Alberta, Canada T2P 4Z4)

  • John Fallis

    (Canadian Pacific Railway, Gulf Canada Square, Suite 400, 401-9th Avenue SW, Calgary, Alberta, Canada T2P 4Z4)

  • Carl Van Dyke

    (MultiModal Applied Systems, Inc., 125 Village Boulevard, Suite 270, Princeton, New Jersey 08540)

  • Jason Kuehn

    (MultiModal Applied Systems, Inc., 125 Village Boulevard, Suite 270, Princeton, New Jersey 08540)

  • Marc Meketon

    (MultiModal Applied Systems, Inc., 125 Village Boulevard, Suite 270, Princeton, New Jersey 08540)

Abstract

North American railways have traditionally practiced tonnage-based dispatching, running trains only when they have enough freight. As a result, their customer service and their use of crews, fixed assets, locomotives, and railcars are poor. Canadian Pacific Railway is using new decision-support tools developed in-house and by MultiModal Applied Systems to create a scheduled railway. These tools use operations research approaches, such as an optimal block-sequencing algorithm, a heuristic algorithm for block design, (very fast) simulation, and time-space network algorithms for planning locomotive use and distributing empty cars. This implementation has saved $300 million Canadian (US$170 million) from mid-1999 through autumn 2000. We estimate it has saved at least an additional $210 million Canadian during 2001 and 2002 in fuel and labor costs alone. Labor productivity, locomotive productivity, fuel consumption, and railcar velocity have improved by 40, 35, 17, and 41 percent, respectively. Furthermore, Canadian Pacific Railway now provides its customers with reliable delivery times and has received many customer and shipping association awards for its improvement in service.

Suggested Citation

  • Phil Ireland & Rod Case & John Fallis & Carl Van Dyke & Jason Kuehn & Marc Meketon, 2004. "The Canadian Pacific Railway Transforms Operations by Using Models to Develop Its Operating Plans," Interfaces, INFORMS, vol. 34(1), pages 5-14, February.
  • Handle: RePEc:inm:orinte:v:34:y:2004:i:1:p:5-14
    DOI: 10.1287/inte.1030.0055
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    References listed on IDEAS

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    Cited by:

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    3. Ralf Borndörfer & Thomas Eßer & Patrick Frankenberger & Andreas Huck & Christoph Jobmann & Boris Krostitz & Karsten Kuchenbecker & Kai Mohrhagen & Philipp Nagl & Michael Peterson & Markus Reuther & Th, 2021. "Deutsche Bahn Schedules Train Rotations Using Hypergraph Optimization," Interfaces, INFORMS, vol. 51(1), pages 42-62, February.
    4. Khaled, Abdullah A. & Jin, Mingzhou & Clarke, David B. & Hoque, Mohammad A., 2015. "Train design and routing optimization for evaluating criticality of freight railroad infrastructures," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 71-84.
    5. Michael F. Gorman & John-Paul Clarke & Amir Hossein Gharehgozli & Michael Hewitt & René de Koster & Debjit Roy, 2014. "State of the Practice: A Review of the Application of OR/MS in Freight Transportation," Interfaces, INFORMS, vol. 44(6), pages 535-554, December.
    6. Endong Zhu & Teodor Gabriel Crainic & Michel Gendreau, 2014. "Scheduled Service Network Design for Freight Rail Transportation," Operations Research, INFORMS, vol. 62(2), pages 383-400, April.
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    9. Chen, C. & Dollevoet, T.A.B. & Zhao, J., 2017. "One-block train formation in large-scale railway networks: An exact model and a tree-based decomposition algorithm," Econometric Institute Research Papers EI-2017-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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