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Managing real-time demand fluctuation under a supplier–retailer coordinated system

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  • Paul, Sanjoy Kumar
  • Sarker, Ruhul
  • Essam, Daryl

Abstract

We have considered a supplier–retailer system, that operates under an agreed coordinated policy, with an imperfect production process and a possibility of having demand fluctuation. In this paper, a dynamic planning process is proposed to deal with short-term demand fluctuations. To do this, a mathematical model was first developed for a single fluctuation, either for increasing or decreasing demand rate. The model generates a revised plan, after the occurrence of the fluctuation event. We also propose a new and efficient heuristic to solve the developed model. Secondly, multiple fluctuations have been considered, for which a new occurrence may or may not affect the revised plan of earlier occurrences and we extend the heuristic so that is capable of dealing with multiple demand fluctuations on a real time basis. We have generated a good number of random test problems and also solved the model using a genetic algorithm, in order to compare the solutions with our heuristic. The comparison confirmed the consistent performance of our developed heuristic, and also its lower computational time. Numerical examples and sensitivity analysis have been presented to explain the usefulness of the developed model.

Suggested Citation

  • Paul, Sanjoy Kumar & Sarker, Ruhul & Essam, Daryl, 2014. "Managing real-time demand fluctuation under a supplier–retailer coordinated system," International Journal of Production Economics, Elsevier, vol. 158(C), pages 231-243.
    • Handle: RePEc:eee:proeco:v:158:y:2014:i:c:p:231-243
    DOI: 10.1016/j.ijpe.2014.08.007
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    Cited by:

    1. Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam, 2018. "A reactive mitigation approach for managing supply disruption in a three-tier supply chain," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1581-1597, October.
    2. Li, Shanshan & He, Yong & Chen, Lujie, 2017. "Dynamic strategies for supply disruptions in production-inventory systems," International Journal of Production Economics, Elsevier, vol. 194(C), pages 88-101.
    3. Md. Tariqul Islam & Abdullahil Azeem & Masum Jabir & Ananna Paul & Sanjoy Kumar Paul, 2022. "An inventory model for a three-stage supply chain with random capacities considering disruptions and supplier reliability," Annals of Operations Research, Springer, vol. 315(2), pages 1703-1728, August.
    4. Paul, Sanjoy Kumar & Chowdhury, Priyabrata & Moktadir, Md. Abdul & Lau, Kwok Hung, 2021. "Supply chain recovery challenges in the wake of COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 136(C), pages 316-329.
    5. Ali, Syed Mithun & Rahman, Md. Hafizur & Tumpa, Tasmia Jannat & Moghul Rifat, Abid Ali & Paul, Sanjoy Kumar, 2018. "Examining price and service competition among retailers in a supply chain under potential demand disruption," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 40-47.
    6. Sanjoy Kumar Paul & Sobhan Asian & Mark Goh & S. Ali Torabi, 2019. "Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss," Annals of Operations Research, Springer, vol. 273(1), pages 783-814, February.
    7. Sarker, Ruhul & Essam, Daryl, 2017. "A quantitative model for disruption mitigation in a supply chainAuthor-Name: Paul, Sanjoy Kumar," European Journal of Operational Research, Elsevier, vol. 257(3), pages 881-895.
    8. Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam & Paul Tae-Woo Lee, 2019. "A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain," Annals of Operations Research, Springer, vol. 280(1), pages 299-335, September.

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