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Dispatch Optimization in Bulk Tanker Transport Operations

Author

Listed:
  • Ted Gifford

    (Engineering and Research, Schneider National, Inc., Green Bay, Wisconsin 54306)

  • Tracy Opicka

    (Engineering and Research, Schneider National, Inc., Green Bay, Wisconsin 54306)

  • Ashesh Sinha

    (Engineering and Research, Schneider National, Inc., Green Bay, Wisconsin 54306)

  • Daniel Vanden Brink

    (Engineering and Research, Schneider National, Inc., Green Bay, Wisconsin 54306)

  • Andy Gifford

    (Engineering and Research, Schneider National, Inc., Green Bay, Wisconsin 54306)

  • Robert Randall

    (Princeton Consultants, Inc., Princeton, New Jersey 08540)

Abstract

All modes of freight transportation are subject to flow imbalances that affect the efficiency of asset utilization. The use of mathematical programming optimization models has a rich history of application to this problem. We use variations and extensions of the classical assignment problem to find globally optimal or near-optimal solutions to the problem of assigning a large number of individual resources (transportation assets) to tasks (freight movements). We address a particularly difficult variant of this problem that occurs in the bulk transport (fuels and chemicals) division of Schneider National Inc. This group accepts 350 customer orders per day, involving 10,000 distinct commodities, with pickup and delivery locations across the continental United States. The corresponding freight movements are executed using a fleet comprising a 1,000 drivers and 1,600 tanker trailers. Chemical interaction properties of these commodities impose complex product-sequencing constraints, interorder tanker wash and preparation processes, and the selection of specific trailer configurations. Schneider National must consider these complexities in addition to those encountered in more common fleet dispatch problems. To address this problem, the engineering group at Schneider National designed and implemented a multiphase, multidimensional matching algorithm and developed new business processes that enable business planners to leverage optimized solution recommendations. We documented over $4 million in annualized operational and capital cost savings, as well as significantly improved productivity and customer service, which this new system has been delivering since its implementation.

Suggested Citation

  • Ted Gifford & Tracy Opicka & Ashesh Sinha & Daniel Vanden Brink & Andy Gifford & Robert Randall, 2018. "Dispatch Optimization in Bulk Tanker Transport Operations," Interfaces, INFORMS, vol. 48(5), pages 403-421, October.
    • Handle: RePEc:inm:orinte:v:48:y:2018:i:5:p:403-421
    DOI: 10.1287/inte.2018.0956
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    References listed on IDEAS

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    1. Subramanian, Anand & Penna, Puca Huachi Vaz & Uchoa, Eduardo & Ochi, Luiz Satoru, 2012. "A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 221(2), pages 285-295.
    2. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "Thirty years of heterogeneous vehicle routing," European Journal of Operational Research, Elsevier, vol. 249(1), pages 1-21.
    3. Hanif D. Sherali & Ki-Hwan Bae & Mohamed Haouari, 2013. "An Integrated Approach for Airline Flight Selection and Timing, Fleet Assignment, and Aircraft Routing," Transportation Science, INFORMS, vol. 47(4), pages 455-476, November.
    4. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    5. Asvin Goel & Thibaut Vidal, 2014. "Hours of Service Regulations in Road Freight Transport: An Optimization-Based International Assessment," Transportation Science, INFORMS, vol. 48(3), pages 391-412, August.
    6. Valentina Cacchiani & Juan-José Salazar-González, 2017. "Optimal Solutions to a Real-World Integrated Airline Scheduling Problem," Transportation Science, INFORMS, vol. 51(1), pages 250-268, February.
    7. Martin Savelsbergh & Marc Sol, 1998. "Drive: Dynamic Routing of Independent Vehicles," Operations Research, INFORMS, vol. 46(4), pages 474-490, August.
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    Cited by:

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