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Flow control in time-varying, random supply chains

Author

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  • Matei, Ion
  • Gueye, Assane
  • Baras, John S.

Abstract

This paper focuses on the logistics aspect of supply chain management. It proposes a randomized flow management algorithm for a time-varying, random, supply chain network. A constrained stochastic optimization problem that maximizes the profit function in terms of the long-run, time-average of the flows in the supply chain is formulated. The algorithm is distributed and based on queueing theory and stochastic Lyapunov analysis concepts. The long-run, time averages of the flows generated by the algorithm can get arbitrarily close to the solution of the aforementioned optimization problem. In support of the theoretical results, numerical simulations are also presented.

Suggested Citation

  • Matei, Ion & Gueye, Assane & Baras, John S., 2015. "Flow control in time-varying, random supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 311-330.
    • Handle: RePEc:eee:transe:v:77:y:2015:i:c:p:311-330
    DOI: 10.1016/j.tre.2015.01.006
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    References listed on IDEAS

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    1. Brian M. Lewis & Alan L. Erera & Maciek A. Nowak & White Chelsea C., 2013. "Managing Inventory in Global Supply Chains Facing Port-of-Entry Disruption Risks," Transportation Science, INFORMS, vol. 47(2), pages 162-180, May.
    2. Hsu, Chaug-Ing & Li, Hui-Chieh, 2011. "Reliability evaluation and adjustment of supply chain network design with demand fluctuations," International Journal of Production Economics, Elsevier, vol. 132(1), pages 131-145, July.
    3. June Dong & Ding Zhang & Anna Nagurney, 2004. "Supply chain supernetworks with random demands," Chapters, in: Der-Horng Lee (ed.), Urban and Regional Transportation Modeling, chapter 16, Edward Elgar Publishing.
    4. Nagurney, Anna, 2010. "Supply chain network design under profit maximization and oligopolistic competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 281-294, May.
    5. Michael K. Lim & Achal Bassamboo & Sunil Chopra & Mark S. Daskin, 2013. "Facility Location Decisions with Random Disruptions and Imperfect Estimation," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 239-249, May.
    6. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    7. Aikens, C. H., 1985. "Facility location models for distribution planning," European Journal of Operational Research, Elsevier, vol. 22(3), pages 263-279, December.
    8. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    9. Vidal, Carlos J. & Goetschalckx, Marc, 2001. "A global supply chain model with transfer pricing and transportation cost allocation," European Journal of Operational Research, Elsevier, vol. 129(1), pages 134-158, February.
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