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Shipment Routing Algorithms with Tree Constraints

Author

Listed:
  • Warren B. Powell

    (Princeton University, School of Engineering and Applied Science, Princeton, New Jersey 08544)

  • Ioannis A. Koskosidis

    (Department of Civil Engineering and The Institute for Transportation Systems, The City College of New York, New York, New York 10031)

Abstract

Routing shipments efficiently on less-than-truckload trucking networks represents an important subproblem of the general network design problem that arises when designing a service network. The objective of the LTL shipment routing problem is to minimize the total transportation and handling costs subject to two key constraints: (i) service between two terminals must always satisfy a given minimum frequency (measured in trailers per week) and (ii) the paths from all origins into a destination should form a tree. This second constraint reflects a practical limitation on the types of instructions that can be implemented in the field. A solution approach is developed using a shortest path based formulation with additional routing constraints imposed to refine the routing in response to minimum frequency constraints. A local improvement heuristic is presented which manipulates the routing constraints. A separate set of primal-dual algorithms are also developed which provide both upper and lower bounds. Numerical experiments are presented to evaluate the effectiveness of both the local improvement heuristic and the primal-dual algorithms.

Suggested Citation

  • Warren B. Powell & Ioannis A. Koskosidis, 1992. "Shipment Routing Algorithms with Tree Constraints," Transportation Science, INFORMS, vol. 26(3), pages 230-245, August.
    • Handle: RePEc:inm:ortrsc:v:26:y:1992:i:3:p:230-245
    DOI: 10.1287/trsc.26.3.230
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    Citations

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    Cited by:

    1. Yan, Shangyao & Young, Hwei-Fwa, 1996. "A decision support framework for multi-fleet routing and multi-stop flight scheduling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(5), pages 379-398, September.
    2. Popken, Douglas A., 1996. "An analytical framework for routing multiattribute multicommodity freight," Transportation Research Part B: Methodological, Elsevier, vol. 30(2), pages 133-145, April.
    3. Ahmad Baubaid & Natashia Boland & Martin Savelsbergh, 2021. "The Value of Limited Flexibility in Service Network Designs," Transportation Science, INFORMS, vol. 55(1), pages 52-74, 1-2.
    4. Lin, Cheng-Chang, 2001. "The freight routing problem of time-definite freight delivery common carriers," Transportation Research Part B: Methodological, Elsevier, vol. 35(6), pages 525-547, July.
    5. Alan Erera & Michael Hewitt & Martin Savelsbergh & Yang Zhang, 2013. "Improved Load Plan Design Through Integer Programming Based Local Search," Transportation Science, INFORMS, vol. 47(3), pages 412-427, August.
    6. Tamvada, Srinivas Subramanya & Mansouri, Bahareh & Hassini, Elkafi & Pribytkov, Theodore, 2021. "An integer programming model and directed Steiner-forest based heuristic for routing less-than-truckload freight," International Journal of Production Economics, Elsevier, vol. 232(C).
    7. Crainic, Teodor Gabriel, 2000. "Service network design in freight transportation," European Journal of Operational Research, Elsevier, vol. 122(2), pages 272-288, April.
    8. Greening, Lacy M. & Dahan, Mathieu & Erera, Alan L., 2023. "Lead-Time-Constrained Middle-Mile Consolidation Network Design with Fixed Origins and Destinations," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).

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