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A Network Flow Based Heuristic for Bulk Pickup and Delivery Routing

Author

Listed:
  • Marshall L. Fisher

    (Department of Decision Sciences, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6366)

  • Baoxing Tang

    (United Airlines, Executive Offices-EXOEB, Chicago, Illinois 60666)

  • Zhang Zheng

    (Department of Industrial Engineering Management, Shanghai Jiao Tong University, Shanghai 20030, Peoples Republic of China)

Abstract

We consider a problem in which a fleet of vehicles must be scheduled to pickup and deliver a set of orders in truckload quantities. We describe a new algorithm based on a network flow relaxation which imposes necessary conditions on the flow of empty vehicles from order delivery points to order pickup points. The network flow model provides a lower bound and a nearly feasible solution that can be made feasible with some simple heuristics. Our algorithm is fast and has performed well on a set of more than 430 test problems which include a number of real problems obtained from the Shanghai Truck Transportation Corporation. On real problems and on random problems generated using real pickup and delivery points, the algorithm consistently produces solutions within 1% of optimality.

Suggested Citation

  • Marshall L. Fisher & Baoxing Tang & Zhang Zheng, 1995. "A Network Flow Based Heuristic for Bulk Pickup and Delivery Routing," Transportation Science, INFORMS, vol. 29(1), pages 45-55, February.
    • Handle: RePEc:inm:ortrsc:v:29:y:1995:i:1:p:45-55
    DOI: 10.1287/trsc.29.1.45
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    Cited by:

    1. Imai, Akio & Nishimura, Etsuko & Current, John, 2007. "A Lagrangian relaxation-based heuristic for the vehicle routing with full container load," European Journal of Operational Research, Elsevier, vol. 176(1), pages 87-105, January.
    2. Yi, Wei & Ozdamar, Linet, 2007. "A dynamic logistics coordination model for evacuation and support in disaster response activities," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1177-1193, June.

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