Cooperative Supply Chain Re-scheduling: The Case of an Engine Supply Chain

  • Jaime Lloret
  • Jose P. Garcia-Sabater
  • Juan A. Marin-Garcia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5738)

Abstract

One of the main issues on task planning of the enterprises with several production sites is how they can reassign tasks when a part of the supply chain is stopped. In this case, a good re-schedule, involving parts from supply chains from other sites, could imply to reduce overall costs. In this paper, we propose a cooperative system to re-schedule a network chain. The algorithm proposed is described and analyzed analytically in detail. The re-schedule decision is taken based on the time and the cost reduction. In order to test its performance and the success of our proposal, we have simulated a stylized system based on an engine network chain using the Anylogic TM simulator. Our proposal allows cooperative multisite re-scheduling by selecting the type of transport for sending components from one site to another based on the costs and the deadline to assemble the final product.

Keywords

Re-scheduling Cooperative decision making Supply chain  cooperative-group-based model 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cordeau, J.F., Pasin, F., Solomon, M.: An integrated model for logistics network design. Annals of Operations Research 144(1), 59–82 (2006)MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Gaudreault, J., Frayret, J.M., Pesant, G.: Distributed search for supply chain coordination. Computers in Industry. Corrected Proof. online March 21 (in Press, 2009)Google Scholar
  3. 3.
    Wang, S., Sarker, B.R.: An assembly-type supply chain system controlled by kanbans under a just-in-time delivery policy. European Journal of Operational Research 162(1), 153–172 (2005)CrossRefMATHGoogle Scholar
  4. 4.
    Christopher, M.: Logistics and Supply Chain Management - Strategies for reducing cost and improving service, 2nd edn., London, Finacial Times, p. 294 (1998)Google Scholar
  5. 5.
    Stadtler, H., Kilger, C.: Supply chain managementnext term and advanced planning: concepts, models, software and case studies, p. 512. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Chern, C.C., Hsieh, J.S.: A heuristic algorithm for master planning that satisfies multiple objectives. Computers & Operations Research 34(11), 3491–3513 (2007)CrossRefMATHGoogle Scholar
  7. 7.
    Lambert, D.M., Cooper, M.C.: Issues in Supply Chain Management. Industrial Marketing Management 29(1), 65–83 (2000)CrossRefGoogle Scholar
  8. 8.
    Surana, A., Kumara, S., Greaves, M., Raghavan, U.N.: Supply-chain networks: a complex adaptive systems perspective. International Journal of Production Research 43(20), 4235–4265 (2005)CrossRefGoogle Scholar
  9. 9.
    Lee, H.L.: Aligning Supply Chain Strategies with Product Uncertainties. California Management Review 44(3), 105–119 (2002)CrossRefGoogle Scholar
  10. 10.
    Narasimhan, R., Talluri, S.: Perspectives on risk management in supply chains. Journal of Operations Management 27(2), 114–118 (2009)CrossRefGoogle Scholar
  11. 11.
    Christopher, M., Peck, H.: Building the resilient supply chain. The International Journal of Logistics Management 15(2), 1–4 (2004)CrossRefGoogle Scholar
  12. 12.
    Lloret, J., Garcia-Sabater, J.P., Marin-Garcia, J.A.: Cooperative multisite production re-scheduling. In: Luo, Y. (ed.) CDVE 2008. LNCS, vol. 5220, pp. 156–163. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jaime Lloret
    • 1
  • Jose P. Garcia-Sabater
    • 2
  • Juan A. Marin-Garcia
    • 2
  1. 1.Departamento de ComunicacionesUniversidad Politécnica de ValenciaValenciaSpain
  2. 2.ROGLE-Departamento de Organización de EmpresasUniversidad Politécnica de ValenciaValenciaSpain

Personalised recommendations