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Queuing Networks and the Topological Design of Supply Chain Systems

Author

Listed:
  • Laoucine Kerbache

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • James Macgregor Smith

    (Department of Mechanical and Industrial Engineering [UMass] - UMass Amherst - University of Massachusetts [Amherst] - UMASS - University of Massachusetts System)

Abstract

Manufacturing firms are linking their internal processes to external suppliers and customers. The resulting supply chain is often a very large network of activities and resources. Modeling and optimization of such complex systems is a new area of research for which exact analytical results are obviously very difficult if not impossible. We develop a methodology based on analytical queueing networks coupled with nonlinear optimization to design supply chain topologies and evaluate various performance measures. The results obtained from small network configurations as well as from the case study discussed in the paper demonstrate that our approach is a very useful tool to analyze congestion problems and to evaluate the performance of the network topologies.

Suggested Citation

  • Laoucine Kerbache & James Macgregor Smith, 2004. "Queuing Networks and the Topological Design of Supply Chain Systems," Post-Print hal-00796346, HAL.
    • Handle: RePEc:hal:journl:hal-00796346
    DOI: 10.1016/j.ijpe.2003.09.002
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    Citations

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    Cited by:

    1. Morabito, Reinaldo & de Souza, Mauricio C. & Vazquez, Mariana, 2014. "Approximate decomposition methods for the analysis of multicommodity flow routing in generalized queuing networks," European Journal of Operational Research, Elsevier, vol. 232(3), pages 618-629.
    2. Saharidis, Georgios K.D. & Kouikoglou, Vassilis S. & Dallery, Yves, 2009. "Centralized and decentralized control polices for a two-stage stochastic supply chain with subcontracting," International Journal of Production Economics, Elsevier, vol. 117(1), pages 117-126, January.
    3. Liang, Wen Yau & Huang, Chun-Che & Lin, Yin-Chen & Chang, Tsun Hsien & Shih, Meng Hao, 2013. "The multi-objective label correcting algorithm for supply chain modeling," International Journal of Production Economics, Elsevier, vol. 142(1), pages 172-178.
    4. Fan, Chin-Yuan & Fan, Pei-Shu & Chang, Pei-Chann, 2010. "A system dynamics modeling approach for a military weapon maintenance supply system," International Journal of Production Economics, Elsevier, vol. 128(2), pages 457-469, December.
    5. Feng, Cheng-Min & Wu, Pei-Ju, 2009. "A tax savings model for the emerging global manufacturing network," International Journal of Production Economics, Elsevier, vol. 122(2), pages 534-546, December.
    6. Awudu, Iddrisu & Zhang, Jun, 2012. "Uncertainties and sustainability concepts in biofuel supply chain management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1359-1368.

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