Abstract
In this chapter, the portfolio approach and SMIP models presented in Chap. 2 are enhanced for the combined selection and protection of part suppliers and order quantity allocation in a supply chain with disruption risks.
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Problems
Problems
4.1
Modify the probability, \(P_{s}\), for disruption scenarios to account for suppliers located in different regions, subject to regional disruptions that may affect all suppliers in the same region simultaneously. Modify the SMIP models presented in this chapter for a joint fortification of all suppliers in one region.
4.2
Define service level for the SMIP models presented in this chapter and modify the models for the service level objective function.
4.3
Limited storage space for emergency inventory
(a) Modify the SMIP models presented in Sect. 4.3 for the resilient supply portfolio with single protection levels to account for limited storage space for emergency inventory at protected suppliers.
(b) Modify the SMIP models presented in Sect. 4.5 for the resilient supply portfolio with multiple protection levels to account for limited storage space for emergency inventory at protected suppliers, dependent on protection level.
4.4
Modify the protection index introduced in Sect. 4.4 for the resilient supply portfolios with multiple protection levels.
4.5
In the computational examples for unreliable suppliers, Table 4.9 and Fig. 4.6b indicate that the risk-averse resilient solutions for confidence levels \(\alpha =0.9,\;0.95,\;0.99\) are very close each other. How, would you explain the reason for that, and what would be the explanation for the case with identical solutions?
Hint: compare with solution results presented in Table 4.5 for a single protection level.
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Sawik, T. (2018). Selection of Resilient Supply Portfolio. In: Supply Chain Disruption Management Using Stochastic Mixed Integer Programming. International Series in Operations Research & Management Science, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-319-58823-0_4
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DOI: https://doi.org/10.1007/978-3-319-58823-0_4
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