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Adaptive direct/indirect delivery decision protocol by collaborative negotiation among manufacturers, distributors, and retailers

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  • Scavarda, Manuel
  • Seok, Hyesung
  • Puranik, Anurag S.
  • Nof, Shimon Y.

Abstract

Recently, as the dynamic nature of supply networks increases, the importance of adaptive design, planning, and management becomes more emphasized. Especially, as the complexity of interacted distributed operations increases under changeable conditions, it becomes a key issue to design the adaptive collaboration strategy considering the multiple network participants׳ economic goals and interdependent factors that affect/restrict their viability. Hence, this paper addresses one of related supply network problems—an adaptive direct/indirect delivery by using appropriate collaboration to deal with changeable conditions. We have developed a Direct/Indirect Delivery Protocol (DIDP), which aids to model physically and economically viable collaboration strategies and provides effective delivery schedule under changeable conditions. This decision protocol is designed based on Collaborative Control Theory (CCT), and includes Delivery Plan Generation sub-protocol (DPGsp) for delivery pattern estimation and optimization process. To evaluate its performance, a numerical example is conducted; it results in accommodating to external changes well with 55% increase in the resources utilization ratio and 20% reduction in the total physical distribution cost, compared to original delivery pattern.

Suggested Citation

  • Scavarda, Manuel & Seok, Hyesung & Puranik, Anurag S. & Nof, Shimon Y., 2015. "Adaptive direct/indirect delivery decision protocol by collaborative negotiation among manufacturers, distributors, and retailers," International Journal of Production Economics, Elsevier, vol. 167(C), pages 232-245.
    • Handle: RePEc:eee:proeco:v:167:y:2015:i:c:p:232-245
    DOI: 10.1016/j.ijpe.2015.05.006
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    References listed on IDEAS

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    1. Velásquez, J.D. & Nof, S.Y., 2009. "Best-matching protocols for assembly in e-work networks," International Journal of Production Economics, Elsevier, vol. 122(1), pages 508-516, November.
    2. Soumia Ichoua & Michel Gendreau & Jean-Yves Potvin, 2006. "Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching," Transportation Science, INFORMS, vol. 40(2), pages 211-225, May.
    3. Barrett W. Thomas, 2007. "Waiting Strategies for Anticipating Service Requests from Known Customer Locations," Transportation Science, INFORMS, vol. 41(3), pages 319-331, August.
    4. Wikner, J. & Towill, D. R. & Naim, M., 1991. "Smoothing supply chain dynamics," International Journal of Production Economics, Elsevier, vol. 22(3), pages 231-248, December.
    5. Yoon, Sang Won & Nof, Shimon Y., 2011. "Affiliation/dissociation decision models in demand and capacity sharing collaborative network," International Journal of Production Economics, Elsevier, vol. 130(2), pages 135-143, April.
    6. Jürgen Branke & Martin Middendorf & Guntram Noeth & Maged Dessouky, 2005. "Waiting Strategies for Dynamic Vehicle Routing," Transportation Science, INFORMS, vol. 39(3), pages 298-312, August.
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    Cited by:

    1. Laurence Saglietto, 2021. "Bibliometric analysis of sharing economy logistics and crowd logistics," Post-Print halshs-03562657, HAL.

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