IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v167y2015icp232-245.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527315001474
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2015.05.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Barrett W. Thomas, 2007. "Waiting Strategies for Anticipating Service Requests from Known Customer Locations," Transportation Science, INFORMS, vol. 41(3), pages 319-331, August.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

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

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marlin W. Ulmer & Justin C. Goodson & Dirk C. Mattfeld & Marco Hennig, 2019. "Offline–Online Approximate Dynamic Programming for Dynamic Vehicle Routing with Stochastic Requests," Service Science, INFORMS, vol. 53(1), pages 185-202, February.
    2. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    3. Ritzinger, Ulrike & Puchinger, Jakob & Rudloff, Christian & Hartl, Richard F., 2022. "Comparison of anticipatory algorithms for a dial-a-ride problem," European Journal of Operational Research, Elsevier, vol. 301(2), pages 591-608.
    4. Marlin W. Ulmer & Dirk C. Mattfeld & Felix Köster, 2018. "Budgeting Time for Dynamic Vehicle Routing with Stochastic Customer Requests," Transportation Science, INFORMS, vol. 52(1), pages 20-37, January.
    5. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    6. Zhang, Jian & Luo, Kelin & Florio, Alexandre M. & Van Woensel, Tom, 2023. "Solving large-scale dynamic vehicle routing problems with stochastic requests," European Journal of Operational Research, Elsevier, vol. 306(2), pages 596-614.
    7. Martijn Mes & Matthieu Heijden & Peter Schuur, 2013. "Interaction between intelligent agent strategies for real-time transportation planning," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(2), pages 337-358, March.
    8. Yiting Xing & Ling Li & Zhuming Bi & Marzena Wilamowska‐Korsak & Li Zhang, 2013. "Operations Research (OR) in Service Industries: A Comprehensive Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 300-353, May.
    9. Berbeglia, Gerardo & Cordeau, Jean-François & Laporte, Gilbert, 2010. "Dynamic pickup and delivery problems," European Journal of Operational Research, Elsevier, vol. 202(1), pages 8-15, April.
    10. Gregorio Tirado & Lars Magnus Hvattum, 2017. "Determining departure times in dynamic and stochastic maritime routing and scheduling problems," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 553-571, December.
    11. Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
    12. Gianpaolo Ghiani & Emanuele Manni & Barrett W. Thomas, 2012. "A Comparison of Anticipatory Algorithms for the Dynamic and Stochastic Traveling Salesman Problem," Transportation Science, INFORMS, vol. 46(3), pages 374-387, August.
    13. Lars M. Hvattum & Arne Løkketangen & Gilbert Laporte, 2006. "Solving a Dynamic and Stochastic Vehicle Routing Problem with a Sample Scenario Hedging Heuristic," Transportation Science, INFORMS, vol. 40(4), pages 421-438, November.
    14. Marlin W. Ulmer & Alan Erera & Martin Savelsbergh, 2022. "Dynamic service area sizing in urban delivery," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 763-793, September.
    15. Marlin W. Ulmer, 2020. "Horizontal combinations of online and offline approximate dynamic programming for stochastic dynamic vehicle routing," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 279-308, March.
    16. Stefan Vonolfen & Michael Affenzeller, 2016. "Distribution of waiting time for dynamic pickup and delivery problems," Annals of Operations Research, Springer, vol. 236(2), pages 359-382, January.
    17. Srour, F.J. & Agatz, N.A.H. & Oppen, J., 2014. "Strategies for Handling Temporal Uncertainty in Pickup and Delivery Problems with Time Windows," ERIM Report Series Research in Management ERS-2014-015-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. Marlin W. Ulmer & Leonard Heilig & Stefan Voß, 2017. "On the Value and Challenge of Real-Time Information in Dynamic Dispatching of Service Vehicles," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(3), pages 161-171, June.
    19. Gharehgozli, Amir & Zaerpour, Nima, 2018. "Stacking outbound barge containers in an automated deep-sea terminal," European Journal of Operational Research, Elsevier, vol. 267(3), pages 977-995.
    20. Zolfagharinia, Hossein & Haughton, Michael, 2016. "Effective truckload dispatch decision methods with incomplete advance load information," European Journal of Operational Research, Elsevier, vol. 252(1), pages 103-121.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:167:y:2015:i:c:p:232-245. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.