IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v41y2013i2p259-269.html
   My bibliography  Save this article

Selection of resilient supply portfolio under disruption risks

Author

Listed:
  • Sawik, Tadeusz

Abstract

This paper deals with the optimal selection and protection of part suppliers and order quantity allocation in a supply chain with disruption risks. The protection decisions include the selection of suppliers to be protected against disruptions and the allocation of emergency inventory of parts to be pre-positioned at the protected suppliers. The decision maker needs to decide which supplier to select for parts delivery and how to allocate orders quantity among the selected suppliers, and which of the selected suppliers to protect against disruptions and how to allocate emergency inventory among the protected suppliers. The problem objective is to achieve a minimum cost of suppliers protection, emergency inventory pre-positioning, parts ordering, purchasing, transportation and shortage and to mitigate the impact of disruption risks by minimizing the potential worst-case cost. As a result a resilient supply portfolio is identified with protected suppliers capable of supplying parts in the face of disruption events. A mixed integer programming approach is proposed to determine risk-neutral, risk-averse or mean-risk supply portfolios, with conditional value-at-risk applied to control the risk of worst-case cost. Numerical examples are presented and some computational results are reported.

Suggested Citation

  • Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
  • Handle: RePEc:eee:jomega:v:41:y:2013:i:2:p:259-269
    DOI: 10.1016/j.omega.2012.05.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030504831200093X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.omega.2012.05.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. P D Berger & A Z Zeng, 2006. "Single versus multiple sourcing in the presence of risks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(3), pages 250-261, March.
    2. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    3. Jenkins, L., 2000. "Selecting scenarios for environmental disaster planning," European Journal of Operational Research, Elsevier, vol. 121(2), pages 275-286, March.
    4. Ruiz-Torres, Alex J. & Mahmoodi, Farzad, 2007. "The optimal number of suppliers considering the costs of individual supplier failures," Omega, Elsevier, vol. 35(1), pages 104-115, February.
    5. Berger, Paul D. & Gerstenfeld, Arthur & Zeng, Amy Z., 2004. "How many suppliers are best? A decision-analysis approach," Omega, Elsevier, vol. 32(1), pages 9-15, February.
    6. Rawls, Carmen G. & Turnquist, Mark A., 2010. "Pre-positioning of emergency supplies for disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 521-534, May.
    7. Schmitt, Amanda J., 2011. "Strategies for customer service level protection under multi-echelon supply chain disruption risk," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1266-1283, September.
    8. Yu, Haisheng & Zeng, Amy Z. & Zhao, Lindu, 2009. "Single or dual sourcing: decision-making in the presence of supply chain disruption risks," Omega, Elsevier, vol. 37(4), pages 788-800, August.
    9. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    10. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Faiza Hamdi & Ahmed Ghorbel & Faouzi Masmoudi & Lionel Dupont, 2018. "Optimization of a supply portfolio in the context of supply chain risk management: literature review," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 763-788, April.
    2. Preetam Basu & Soumita Ghosh & Milan Kumar, 2019. "Supplier ratings and dynamic sourcing strategies to mitigate supply disruption risks," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 46(1), pages 41-57, March.
    3. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    4. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    5. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2017. "An assessment of supply chain disruption mitigation strategies," International Journal of Production Economics, Elsevier, vol. 184(C), pages 210-230.
    6. Li, Shanshan & He, Yong & Chen, Lujie, 2017. "Dynamic strategies for supply disruptions in production-inventory systems," International Journal of Production Economics, Elsevier, vol. 194(C), pages 88-101.
    7. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    8. Maheswar Singh Mahapatra & Pravash Chandra Pradhan & J. K. Jha, 2022. "Sourcing decisions with order allocation under supply disruption risk considering quantitative and qualitative criteria," Operational Research, Springer, vol. 22(4), pages 3291-3333, September.
    9. Roni, Mohammad S. & Jin, Mingzhou & Eksioglu, Sandra D., 2015. "A hybrid inventory management system responding to regular demand and surge demand," Omega, Elsevier, vol. 52(C), pages 190-200.
    10. Sawik, Tadeusz, 2014. "Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing," Omega, Elsevier, vol. 43(C), pages 83-95.
    11. Sawik, Tadeusz, 2015. "On the fair optimization of cost and customer service level in a supply chain under disruption risks," Omega, Elsevier, vol. 53(C), pages 58-66.
    12. Fattahi, Mohammad, 2021. "Resilient procurement planning for supply chains: A case study for sourcing a critical mineral material," Resources Policy, Elsevier, vol. 74(C).
    13. Zeng, Amy Z. & Xia, Yu, 2015. "Building a mutually beneficial partnership to ensure backup supply," Omega, Elsevier, vol. 52(C), pages 77-91.
    14. Xia, Yu, 2011. "Competitive strategies and market segmentation for suppliers with substitutable products," European Journal of Operational Research, Elsevier, vol. 210(2), pages 194-203, April.
    15. Tadeusz Sawik, 2018. "Selection of a dynamic supply portfolio under delay and disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 760-782, January.
    16. Mohammaddust, Faeghe & Rezapour, Shabnam & Farahani, Reza Zanjirani & Mofidfar, Mohammad & Hill, Alex, 2017. "Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 632-653.
    17. Wagner, Stephan M. & Bode, Christoph & Koziol, Philipp, 2011. "Negative default dependence in supplier networks," International Journal of Production Economics, Elsevier, vol. 134(2), pages 398-406, December.
    18. Meena, P.L. & Sarmah, S.P. & Sarkar, A., 2011. "Sourcing decisions under risks of catastrophic event disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1058-1074.
    19. Ray, Pritee & Jenamani, Mamata, 2016. "Mean-variance analysis of sourcing decision under disruption risk," European Journal of Operational Research, Elsevier, vol. 250(2), pages 679-689.
    20. Wagner, Stephan M. & Bode, Christoph & Koziol, Philipp, 2009. "Supplier default dependencies: Empirical evidence from the automotive industry," European Journal of Operational Research, Elsevier, vol. 199(1), pages 150-161, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jomega:v:41:y:2013:i:2:p:259-269. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.