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Supply Chain Disruptions Preparedness Measures Using a Dynamic Model

  • Amit SonarEmail author
  • Cameron A. Mackenzie
Chapter

Abstract

Supply chain risk management has recently seen extensive research efforts, but questions such as “How should a firm plan for each type of disruption?” and “What are the strategies and the total cost incurred by the firm if a disruption occurs?” continue to deserve attention. This chapter analyzes different disruption cases by considering the impacts of disruptions at a supplier, a firm’s warehouse, and at the firm’s production facility. The firm can prepare for each type of disruption by buying from an alternate supplier, holding more inventory, or holding inventory at a different warehouse. The Wagner-Whitin model is used to solve the optimal ordering strategy for each type of disruption. Since the type of disruption is uncertain, we assign probabilities for each disruption and use the Wagner-Whitin model to find the order policy that minimizes the firm’s expected cost.

References

  1. Adhyitya, A., Srinivasan, R., & Karimi, I. A. (2007). Heuristic rescheduling of crude oil operations to manage abnormal supply chain events. American Institute of Chemical Engineers Journal, 53(2), 397–422.CrossRefGoogle Scholar
  2. Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm’s resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33, 111–122.CrossRefGoogle Scholar
  3. Babich, V., Burnetas, A. N., & Ritchken, P. H. (2007). Competition and diversification effects in supply chains with supplier default risk. Manufacturing & Service Operations Management, 9(2), 123–146.CrossRefGoogle Scholar
  4. Bean, J. C., Birge, J. R., Mittenthal, J., & Noon, C. E. (1991). Matchup scheduling with multiple resources, release dates and disruptions. Operations Research, 39(3), 470–483.CrossRefGoogle Scholar
  5. Bode, C., & Wagner, S. M. (2015). Structural drivers of upstream supply chain complexity and the frequency of supply chain disruptions. Journal of Operations Management, 36, 215–228.CrossRefGoogle Scholar
  6. Hendricks, K. B., Singhal, V. R., & Zhang, R. (2009). The effect of operational slack, diversification, and vertical relatedness on the stock market reaction to supply chain disruptions. Journal of Operations Management, 27(3), 233–246.CrossRefGoogle Scholar
  7. Hopp WJ, Iravani SMR, Liu Z (2009) Strategic risk from supply chain disruptions. Working paper. Department of Industrial Engineering and Management Sciences, Northwestern University. Retrieved from http://webuser.bus.umich.edu/whopp/working%20papers/Strategic%20Risk%20from%20Supply%20Chain%20Disruptions.pdf
  8. Hopp, W. J., & Spearman, M. L. (2008). Factory physics (3rd ed.). Boston, MA: McGraw-Hill.Google Scholar
  9. Jeunet, J., & Jonard, N. (2000). Measuring the performance of lot-sizing techniques in uncertain environments. International Journal of Production Economics, 64(1), 197–208.CrossRefGoogle Scholar
  10. Kazan, O., Nagi, R., & Rump, C. M. (2000). New lot-sizing formulations for less nervous production schedules. Computers & Operations Research, 27(13), 1325–1345.CrossRefGoogle Scholar
  11. MacKenzie CA, Barker K, Grant FH (2012) Evaluating the consequences of an inland waterway port closure with a dynamic multiregional interdependence model. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, 42(2), 359–370.Google Scholar
  12. MacKenzie, C. A., Barker, K., & Santos, J. R. (2014). Modeling a severe supply chain disruption and post-disaster decision making with application to the Japanese earthquake and tsunami. IIE Transactions, 46(12), 1243–1260.CrossRefGoogle Scholar
  13. Natarajarathinam, M., Capar, I., & Narayanan, A. (2009). Managing supply chains in times of crisis: A review of literature and insights. International Journal of Physical Distribution & Logistics Management, 39(7), 535–573.CrossRefGoogle Scholar
  14. Papadakis, I. S. (2006). Financial performance of supply chains after disruptions: An event study. Supply Chain Management: An International Journal, 11(1), 25–33.CrossRefGoogle Scholar
  15. Richter, K., & Weber, J. (2001). The reverse Wagner/Whitin model with variable manufacturing and remanufacturing cost. International Journal of Production Economics, 71, 447–456.CrossRefGoogle Scholar
  16. Richter, K., & Sombrutzki, M. (2000). Remanufacturing planning for the reverse Wagner/Whitin models. European Journal of Operational Research, 121(2), 304–315.CrossRefGoogle Scholar
  17. Sheffi, Y. (2005). The resilient enterprise: Overcoming vulnerability for competitive advantage. Cambridge: The MIT Press.Google Scholar
  18. Schmitt, A. J., & Tomlin, B. (2012). Sourcing strategies to manage supply disruptions. In H. Gurnani, A. Mehrotra, & S. Ray (Eds.), supply chain disruptions: Theory and practice of managing risk (pp. 51–72). London: Springer.CrossRefGoogle Scholar
  19. Snyder, L. V., Atan, Z., Peng, P., Rong, Y., Schmitt, A. J., & Sinsoysal, B. (2016). OR/MS models for supply chain disruptions: A review. IIE Transactions, 48(2), 89–109.CrossRefGoogle Scholar
  20. Snyder LV, Scaparra MP, Daskin MS, Church RL (2006) Planning for disruptions in supply chain networks. Tutorials in Operations Research, 234–257.Google Scholar
  21. Song, J.-S., & Zipkin, P. H. (1996). Inventory control with information about supply conditions. Management Science, 42(10), 1409–1419.CrossRefGoogle Scholar
  22. Song, J.-S., & Zipkin, P. (2009). Inventories with multiple supply sources and networks of queues with overflow bypasses. Management Science, 55(3), 362–372.CrossRefGoogle Scholar
  23. Tang, C. S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103(2), 451–488.CrossRefGoogle Scholar
  24. Tomlin, B. (2006). On the value of mitigation and contingency strategies for managing supply chain disruption risks. Management Science, 52(5), 639–657.CrossRefGoogle Scholar
  25. Vakharia, A. J., & Yenipazarli, A. (2008). Managing supply chain disruptions. Foundations and Trends in Technology, Information and Operations Management, 2(4), 243–325.CrossRefGoogle Scholar
  26. Wagner, H. M., & Whitin, T. M. (1958). Dynamic version of the economic lot size model. Management Science, 9(1), 89–96.CrossRefGoogle Scholar
  27. Xia, Y., Yang, M.-H., Golany, B., Gilbert, S. M., & Yu, G. (2004). Real-time disruption management in a two-stage production and inventory system. IIE Transactions, 36, 111–125.CrossRefGoogle Scholar
  28. Xiao, T., & Qi, X. (2008). Price competition, cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailers. Omega, 36(5), 741–753.CrossRefGoogle Scholar
  29. Xiao, T., & Yu, G. (2006). Supply chain disruption management and evolutionarily stable strategies of retailers in the quantity-setting duopoly situation with homogeneous goods. European Journal of Operational Research, 173(2), 648–668.CrossRefGoogle Scholar
  30. Xiao, T., Yu, G., Sheng, Z., & Xia, Y. (2005). Coordination of a supply chain with one-manufacturer and two-retailers under demand promotion and disruption management decisions. Annals of Operations Research, 135(1), 87–109.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Industrial and Manufacturing Systems EngineeringIowa State UniversityAmesUSA

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