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Hub Group Implements a Suite of OR Tools to Improve Its Operations

Author

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  • Michael F. Gorman

    (Department of Management Information Systems, Operations Management and Decision Sciences, University of Dayton, Dayton, Ohio 45419)

Abstract

Hub Group, a North American intermodal freight rail transportation company, developed an integrated production decision support system to improve its yield management and container allocation. The system combines a suite of analytical tools, including forecasting, error distribution analysis, expected value-based heuristics, and optimization tools to improve the decision making of Hub's frontline employees. It is important to note that the production decision support system was structured to fit within Hub's existing organizational structure, business processes, and information technology systems to reduce project risk, development costs, and operational disruption. In 2008, the system's first full year of use, Hub improved its revenue per load by 3 percent and increased its container velocity by 5 percent. These improvements led to a net return of $11 million in cost savings, which equals 22 times Hub's initial investment during that first year of operation.

Suggested Citation

  • Michael F. Gorman, 2010. "Hub Group Implements a Suite of OR Tools to Improve Its Operations," Interfaces, INFORMS, vol. 40(5), pages 368-384, October.
    • Handle: RePEc:inm:orinte:v:40:y:2010:i:5:p:368-384
    DOI: 10.1287/inte.1100.0507
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    References listed on IDEAS

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    1. Michael F. Gorman & Sanjay Ahire, 2006. "A Major Appliance Manufacturer Rethinks Its Inventory Policies for Service Vehicles," Interfaces, INFORMS, vol. 36(5), pages 407-419, October.
    2. Michael F. Gorman & Dharma Acharya & David Sellers, 2010. "CSX Railway Uses OR to Cash In on Optimized Equipment Distribution," Interfaces, INFORMS, vol. 40(1), pages 5-16, February.
    3. Daniel Adelman, 2007. "Price-Directed Control of a Closed Logistics Queueing Network," Operations Research, INFORMS, vol. 55(6), pages 1022-1038, December.
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    Cited by:

    1. Michael F. Gorman, 2021. "Contextual Complications in Analytical Modeling: When the Problem is Not the Problem," Interfaces, INFORMS, vol. 51(4), pages 245-261, July.
    2. Wang, Xinchang, 2017. "Static and dynamic resource allocation models for single-leg transportation markets with service disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 87-108.
    3. Long Gao & Jim (Junmin) Shi & Michael F. Gorman & Ting Luo, 2020. "Business Analytics for Intermodal Capacity Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 310-329, March.
    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. 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.
    6. Wang, Xinchang, 2016. "Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 334-357.
    7. Wang, Xinchang, 2016. "Optimal allocation of limited and random network resources to discrete stochastic demands for standardized cargo transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 310-331.
    8. Wang, Hua & Wang, Xinchang & Zhang, Xiaoning, 2017. "Dynamic resource allocation for intermodal freight transportation with network effects: Approximations and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 83-112.

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