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An Optimization Model for Empty Freight Car Assignment at Union Pacific Railroad

Author

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  • Amar Kumar Narisetty

    (Department of Industrial Engineering, Purdue University, West Lafayette, Indiana 47907)

  • Jean-Philippe P. Richard

    (Department of Industrial Engineering, Purdue University, West Lafayette, Indiana 47907)

  • David Ramcharan

    (Customer Product---Operations Support, IT, Union Pacific Railroad, Omaha, Nebraska 68179)

  • Deby Murphy

    (Interline Equipment Management, Union Pacific Railroad, Omaha, Nebraska 68179)

  • Gayle Minks

    (Interline Equipment Management, Union Pacific Railroad, Omaha, Nebraska 68179)

  • Jim Fuller

    (Golden Years Consulting Services, Omaha, Nebraska 68154)

Abstract

Railroad companies face a difficult problem in assigning empty freight cars based on customer demand because these assignments depend on a variety of factors; these include the location of available empty cars, the urgency of the demand, and the possibilities of car substitution. In this paper, we present an optimization model implemented at Union Pacific Railroad (UP) to assign empty freight cars based on demand. The model seeks to reduce transportation costs, and improve delivery time and customer satisfaction. UP currently uses the model to make real-time assignments in a total car-management system. The model has helped UP to achieve significant reductions in its transportation costs, similar to the savings that our simulation study predicted. In addition, UP reduced the staff required for its demand fulfillment process, resulting in an ROI of 35 percent.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:orinte:v:38:y:2008:i:2:p:89-102
    DOI: 10.1287/inte.1070.0330
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    References listed on IDEAS

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    Cited by:

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    2. 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).
    3. Ioannou, Petros & Giuliano, Genevieve & Dessouky, Maged & Chen, Pengfei & Dexter, Sue, 2020. "Freight Load Balancing and Efficiencies in Alternative Fuel Freight Modes," Institute of Transportation Studies, Working Paper Series qt3ns4b894, Institute of Transportation Studies, UC Davis.
    4. 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.
    5. Milenković, Miloš S. & Bojović, Nebojša J. & Švadlenka, Libor & Melichar, Vlastimil, 2015. "A stochastic model predictive control to heterogeneous rail freight car fleet sizing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 162-198.
    6. Scheffler, Martin & Neufeld, Janis S. & Hölscher, Michael, 2020. "An MIP-based heuristic solution approach for the locomotive assignment problem focussing on (dis-)connecting processes," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 64-80.
    7. 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.
    8. Zhang, Jinchuan & Yang, Hao & Wei, Yuguang & Shang, Pan, 2016. "The empty wagons adjustment algorithm of Chinese heavy-haul railway," Chaos, Solitons & Fractals, Elsevier, vol. 89(C), pages 91-99.
    9. Andrew G. Clark & Susan Cholette & Ozgur Ozluk, 2011. "UCSF Increases Consumer Value Through Optimal Vendor-Show Scheduling," Interfaces, INFORMS, vol. 41(4), pages 327-337, August.
    10. Michael F. Gorman, 2016. "From Magnum Opus to Mea Culpa: A Cautionary Tale of Lessons Learned from a Failed Decision Support System," Interfaces, INFORMS, vol. 46(2), pages 183-195, April.
    11. Kirschstein, Thomas, 2018. "Rail transportation planning in the chemical industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 142-160.
    12. Ruhollah Heydari & Emanuel Melachrinoudis, 2017. "A path-based capacitated network flow model for empty railcar distribution," Annals of Operations Research, Springer, vol. 253(2), pages 773-798, June.

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