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OR Practice---Supporting 3PL Decisions in the Automotive Industry by Generating Diverse Solutions to a Large-Scale Location-Routing Problem

Author

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  • Patrick Schittekat

    (University of Antwerp, 2000 Antwerp, Belgium, and ORTEC)

  • Kenneth Sörensen

    (University of Antwerp, 2000 Antwerp, Belgium)

Abstract

For the distribution of spare parts to car dealers, many automotive companies use a transport network of intermediate hubs or transport platforms, operated by a set of third-party logistics (3PL) partners. The optimization of this network, particularly the selection of 3PL providers and corresponding transport platforms, is a complex decision that needs to be supported by appropriate software tools. In this paper, we develop such a tool, implement it, and show its results on a real-life case study provided by Toyota. The tool is currently in active use at Toyota to study and improve the distribution of spare parts in Germany. Using a tabu search metaheuristic, the developed tool essentially solves a large location-routing problem, but has several innovative features to increase its usefulness. First, the tool generates a set of high-quality but structurally different solutions, rather than a single one. This increases Toyota's negotiating power, increases its ability to analyze its current transport network against possible alternatives, and allows it to quickly switch between different transport networks if unexpected events occur. Second, a commercial vehicle-routing solver is integrated into the tool, to allow for a far more realistic modeling of the vehicle-routing decision.

Suggested Citation

  • Patrick Schittekat & Kenneth Sörensen, 2009. "OR Practice---Supporting 3PL Decisions in the Automotive Industry by Generating Diverse Solutions to a Large-Scale Location-Routing Problem," Operations Research, INFORMS, vol. 57(5), pages 1058-1067, October.
    • Handle: RePEc:inm:oropre:v:57:y:2009:i:5:p:1058-1067
    DOI: 10.1287/opre.1080.0633
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    References listed on IDEAS

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    Cited by:

    1. Thierry Petit & Andrew C. Trapp, 2019. "Enriching Solutions to Combinatorial Problems via Solution Engineering," INFORMS Journal on Computing, INFORMS, vol. 31(3), pages 429-444, July.
    2. Ponboon, Sattrawut & Qureshi, Ali Gul & Taniguchi, Eiichi, 2016. "Branch-and-price algorithm for the location-routing problem with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 1-19.
    3. Nasrin Asgari & Mohsen Rajabi & Masoumeh Jamshidi & Maryam Khatami & Reza Zanjirani Farahani, 2017. "A memetic algorithm for a multi-objective obnoxious waste location-routing problem: a case study," Annals of Operations Research, Springer, vol. 250(2), pages 279-308, March.
    4. Xiangfeng Chen & Gangshu (George) Cai & Jing-Sheng Song, 2019. "The Cash Flow Advantages of 3PLs as Supply Chain Orchestrators," Manufacturing & Service Operations Management, INFORMS, vol. 21(2), pages 435-451, May.
    5. Emrah Demir & Tom Van Woensel & Ton de Kok, 2014. "Multidepot Distribution Planning at Logistics Service Provider Nabuurs B.V," Interfaces, INFORMS, vol. 44(6), pages 591-604, December.

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