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Distribution Coordination Between Suppliers and Customers with a Consolidation Center

Author

Listed:
  • Haiqing Song

    (Lingnan College, Sun Yat-sen University, Guangzhou, China 510275)

  • Vernon N. Hsu

    (Australian School of Business, The University of New South Wales, Sydney, Australia, and School of Management, George Mason University, Fairfax, Virginia 22030)

  • Raymond K. Cheung

    (Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology, Hong Kong, China)

Abstract

We study a problem faced by a third-party logistics provider (3PL) who needs to coordinate shipments between suppliers and customers through a consolidation center in a distribution network. Products from a supplier have one release time and are consolidated into a single shipment to the consolidation center. At the center, products to the same destination are also consolidated into a single shipment, and the consolidation time can be as early as possible or as late as possible, depending on the customer requirement and cost structure. The 3PL needs to determine the pickup times from the suppliers, delivery times to the customers, and the transportation options while considering product release times, latest arrival times, different consolidation policies, and the transportation and storage costs involved. In this paper, we formulate this problem as a nonlinear optimization problem, show it is an NP-hard problem, and develop a dual-based solution method for the general problem. Utilizing the problem's special structure, we show that the Lagrangian dual of the general problem can be solved optimally as a linear program, thus allowing us to accelerate the computation of a lower bound to the optimal objective function value. The experimental results show that the dual-based algorithm provides solutions with objective function values, which are on average within 3.24% of optimality. We also consider a version of the problem where each customer orders products from all suppliers, for which we develop a polynomial-time algorithm.

Suggested Citation

  • Haiqing Song & Vernon N. Hsu & Raymond K. Cheung, 2008. "Distribution Coordination Between Suppliers and Customers with a Consolidation Center," Operations Research, INFORMS, vol. 56(5), pages 1264-1277, October.
  • Handle: RePEc:inm:oropre:v:56:y:2008:i:5:p:1264-1277
    DOI: 10.1287/opre.1070.0488
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    References listed on IDEAS

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    Cited by:

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    4. 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.
    5. Cai, Xiaoqiang & Chen, Jian & Xiao, Yongbo & Xu, Xiaolin & Yu, Gang, 2013. "Fresh-product supply chain management with logistics outsourcing," Omega, Elsevier, vol. 41(4), pages 752-765.
    6. Lixin Tang & Feng Li & Zhi-Long Chen, 2019. "Integrated Scheduling of Production and Two-Stage Delivery of Make-to-Order Products: Offline and Online Algorithms," INFORMS Journal on Computing, INFORMS, vol. 31(3), pages 493-514, July.
    7. Yajun Zhan & Yiping Jiang, 2022. "Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    8. Amin Abbasi-Pooya & Michael T. Lash, 2024. "The third party logistics provider freight management problem: a framework and deep reinforcement learning approach," Annals of Operations Research, Springer, vol. 339(1), pages 965-1024, August.
    9. Aguezzoul, Aicha, 2014. "Third-party logistics selection problem: A literature review on criteria and methods," Omega, Elsevier, vol. 49(C), pages 69-78.

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