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Solving a Freight Transport Problem Using Facility Location Techniques

Author

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  • John G. Klincewicz

    (AT&T Bell Laboratories, Holmdel, New Jersey)

Abstract

Use of consolidation terminals to transport products from various sources to various destinations can take advantage of economies of scale in transportation costs. Instead of making direct shipments, each source can ship in bulk to one or more consolidation terminals. There, shipments can be broken down, and material bound for the same destination can be combined. We consider such a freight transport problem (FTP). For each source–destination pair, it must be decided whether to ship the product directly or via a consolidation terminal. Shipping costs are piecewise linear concave functions of the volume shipped. Shipping via a terminal can also incur a linear inventory holding cost. We seek a minimum cost pattern of direct and indirect (i.e., via a terminal) shipments. This is a type of concave cost multiproduct network flow problem. We can solve this problem optimally if either the source-to-terminal or the terminal-to-destination shipping costs are linear. In this case, FTP decomposes into a set of concave cost facility location problems (CFLP). In more general cases, heuristic methods that solve sequences of linear problems can be used. Some computational results are presented.

Suggested Citation

  • John G. Klincewicz, 1990. "Solving a Freight Transport Problem Using Facility Location Techniques," Operations Research, INFORMS, vol. 38(1), pages 99-109, February.
    • Handle: RePEc:inm:oropre:v:38:y:1990:i:1:p:99-109
    DOI: 10.1287/opre.38.1.99
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    Cited by:

    1. Qin, Hu & Zhang, Zizhen & Qi, Zhuxuan & Lim, Andrew, 2014. "The freight consolidation and containerization problem," European Journal of Operational Research, Elsevier, vol. 234(1), pages 37-48.
    2. Cardinaels, Eddy, 2008. "The interplay between cost accounting knowledge and presentation formats in cost-based decision-making," Accounting, Organizations and Society, Elsevier, vol. 33(6), pages 582-602, August.
    3. Baumgartner, Kerstin & Fuetterer, André & Thonemann, Ulrich W., 2012. "Supply chain design considering economies of scale and transport frequencies," European Journal of Operational Research, Elsevier, vol. 218(3), pages 789-800.
    4. Baita, Flavio & Ukovich, Walter & Pesenti, Raffaele & Favaretto, Daniela, 1998. "Dynamic routing-and-inventory problems: a review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(8), pages 585-598, November.
    5. Troncoso, Juan J. & Garrido, Rodrigo A., 2005. "Forestry production and logistics planning: an analysis using mixed-integer programming," Forest Policy and Economics, Elsevier, vol. 7(4), pages 625-633, May.
    6. Nowak, Maciek & Hewitt, Mike & Bachour, Hussam, 2019. "Mileage bands in freight transportation," European Journal of Operational Research, Elsevier, vol. 272(2), pages 549-564.
    7. Aykin, Turgut, 1995. "The hub location and routing problem," European Journal of Operational Research, Elsevier, vol. 83(1), pages 200-219, May.
    8. Hanbazazah, Abdulkader S. & Abril, Luis & Erkoc, Murat & Shaikh, Nazrul, 2019. "Freight consolidation with divisible shipments, delivery time windows, and piecewise transportation costs," European Journal of Operational Research, Elsevier, vol. 276(1), pages 187-201.

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