IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v84y2019icp232-248.html
   My bibliography  Save this article

Disruption mitigation and recovery in supply chains using portfolio approach

Author

Listed:
  • Sawik, Tadeusz

Abstract

An innovative portfolio approach and stochastic MIP formulations with an embedded network flow problem are developed for selection of primary and recovery suppliers and assembly plants in the presence of supply chain disruption risks. Local and regional multi-level disruptions of suppliers and assembly plants are considered. Unlike most of reported research on supply chain disruption management a disruptive event is assumed to impact both a primary supplier of parts and the buyer’s firm primary assembly plant. Then the firm may choose alternate (recovery) suppliers and move production to alternate (recovery) plants along with transshipment of parts from the impacted primary plant to the recovery plants. The resulting allocation of unfulfilled demand for parts among recovery suppliers and unfulfilled demand for products among recovery assembly plants determines recovery supply and demand portfolio, respectively. The selection of supply and demand portfolios is determined simultaneously with production scheduling in assembly plants. An integrated decision-making approach with the perfect information about the potential future disruption scenarios is compared with a hierarchical approach with no such information available ahead of time. In the integrated approach a two-stage stochastic model is applied, in which the first stage decision considers disruption scenarios to happen in the second stage so that the impact of disruption risks is mitigated. The second stage decision optimizes the supply chain recovery process. The scenario analysis indicates that for the hierarchical approach the best-case and worst-case disruption scenarios are, respectively subsets and supersets of the corresponding scenarios for the integrated approach. In addition to risk-neutral decision-making based on expected cost or expected service level optimization, an integrated risk-averse approach is developed using CVaR risk measure. The findings indicate that the developed portfolio approach leads to computationally efficient MIP models with a very strong LP relaxation.

Suggested Citation

  • Sawik, Tadeusz, 2019. "Disruption mitigation and recovery in supply chains using portfolio approach," Omega, Elsevier, vol. 84(C), pages 232-248.
    • Handle: RePEc:eee:jomega:v:84:y:2019:i:c:p:232-248
    DOI: 10.1016/j.omega.2018.05.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048316309665
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2018.05.006?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. Tadeusz Sawik, 2017. "A portfolio approach to supply chain disruption management," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1970-1991, April.
    2. Ivanov, Dmitry & Pavlov, Alexander & Dolgui, Alexandre & Pavlov, Dmitry & Sokolov, Boris, 2016. "Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 7-24.
    3. Tadeusz Sawik, 2018. "Supply Chain Disruption Management Using Stochastic Mixed Integer Programming," International Series in Operations Research and Management Science, Springer, number 978-3-319-58823-0, September.
    4. 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.
    5. Matsuo, Hirofumi, 2015. "Implications of the Tohoku earthquake for Toyota׳s coordination mechanism: Supply chain disruption of automotive semiconductors," International Journal of Production Economics, Elsevier, vol. 161(C), pages 217-227.
    6. Jenkins, L., 2000. "Selecting scenarios for environmental disaster planning," European Journal of Operational Research, Elsevier, vol. 121(2), pages 275-286, March.
    7. Freeman, Nickolas & Mittenthal, John & Keskin, Burcu & Melouk, Sharif, 2018. "Sourcing strategies for a capacitated firm subject to supply and demand uncertainty," Omega, Elsevier, vol. 77(C), pages 127-142.
    8. Cameron A. MacKenzie & Kash Barker & Joost R. Santos, 2014. "Modeling a severe supply chain disruption and post-disaster decision making with application to the Japanese earthquake and tsunami," IISE Transactions, Taylor & Francis Journals, vol. 46(12), pages 1243-1260, December.
    9. Tadeusz Sawik, 2019. "Two-period vs. multi-period model for supply chain disruption management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(14), pages 4502-4518, July.
    10. Park, YoungWon & Hong, Paul & Roh, James Jungbae, 2013. "Supply chain lessons from the catastrophic natural disaster in Japan," Business Horizons, Elsevier, vol. 56(1), pages 75-85.
    11. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    12. Zeng, Amy Z. & Xia, Yu, 2015. "Building a mutually beneficial partnership to ensure backup supply," Omega, Elsevier, vol. 52(C), pages 77-91.
    13. 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.
    14. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    15. David Simchi-Levi & William Schmidt & Yehua Wei & Peter Yun Zhang & Keith Combs & Yao Ge & Oleg Gusikhin & Michael Sanders & Don Zhang, 2015. "Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain," Interfaces, INFORMS, vol. 45(5), pages 375-390, October.
    16. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    17. Lawrence V. Snyder & Zümbül Atan & Peng Peng & Ying Rong & Amanda J. Schmitt & Burcu Sinsoysal, 2016. "OR/MS models for supply chain disruptions: a review," IISE Transactions, Taylor & Francis Journals, vol. 48(2), pages 89-109, February.
    18. PrasannaVenkatesan, S. & Goh, M., 2016. "Multi-objective supplier selection and order allocation under disruption risk," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 124-142.
    19. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhu, Xiaoyan & Cao, Yunzhi, 2021. "The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    2. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    3. Sawik, Tadeusz, 2021. "On the risk-averse selection of resilient multi-tier supply portfolio," Omega, Elsevier, vol. 101(C).
    4. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).
    5. Bonnín Roca, Jaime & Vaishnav, Parth & Morgan, Granger M. & Fuchs, Erica & Mendonça, Joana, 2021. "Technology Forgiveness: Why emerging technologies differ in their resilience to institutional instability," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    6. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry, 2023. "Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments," Omega, Elsevier, vol. 117(C).
    7. Paul, Sanjoy Kumar & Chowdhury, Priyabrata & Moktadir, Md. Abdul & Lau, Kwok Hung, 2021. "Supply chain recovery challenges in the wake of COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 136(C), pages 316-329.
    8. Gupta, Varun & Ivanov, Dmitry & Choi, Tsan-Ming, 2021. "Competitive pricing of substitute products under supply disruption," Omega, Elsevier, vol. 101(C).
    9. Cao, Yunzhi & Zhu, Xiaoyan & Yan, Houmin, 2022. "Data-driven Wasserstein distributionally robust mitigation and recovery against random supply chain disruption," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    10. Huang, Hongfu & He, Yong & Li, Dong & Li, Shanshan, 2023. "Competing multinationals’ backshoring decisions: Tax arbitrage versus production reliability tradeoff," European Journal of Operational Research, Elsevier, vol. 311(2), pages 515-532.
    11. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    12. Zheng, Rui & Shou, Biying & Yang, Jun, 2021. "Supply disruption management under consumer panic buying and social learning effects," Omega, Elsevier, vol. 101(C).
    13. Ming Liu & Hao Tang & Yunfeng Wang & Ruixi Li & Yi Liu & Xin Liu & Yaqian Wang & Yiyang Wu & Yu Wu & Zhijun Sun, 2023. "Enhancing Food Supply Chain in Green Logistics with Multi-Level Processing Strategy under Disruptions," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    14. Soumya Kanti Hota & Biswajit Sarkar & Santanu Kumar Ghosh, 2020. "Effects of Unequal Lot Size and Variable Transportation in Unreliable Supply Chain Management," Mathematics, MDPI, vol. 8(3), pages 1-24, March.
    15. Hu, Shaolong & Dong, Zhijie Sasha & Lev, Benjamin, 2022. "Supplier selection in disaster operations management: Review and research gap identification," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    16. Freeman, Nickolas K. & Narayanan, Arunachalam & Keskin, Burcu B., 2021. "Optimal use of downward substitution in a manufacturing operation subject to uncertainty," Omega, Elsevier, vol. 103(C).
    17. Bao, Xing & Diabat, Ali & Zheng, Zhongliang, 2020. "An ambiguous manager's disruption decisions with insufficient data in recovery phase," International Journal of Production Economics, Elsevier, vol. 221(C).
    18. Gast, Johannes & Wehrle, Rebecca & Wiens, Marcus & Schultmann, Frank, 2020. "Impact of notification time on risk mitigation in inland waterway transport," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 247-278, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    19. Belhadi, Amine & Kamble, Sachin & Jabbour, Charbel Jose Chiappetta & Gunasekaran, Angappa & Ndubisi, Nelson Oly & Venkatesh, Mani, 2021. "Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    20. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.

    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. Sawik, Tadeusz, 2021. "On the risk-averse selection of resilient multi-tier supply portfolio," Omega, Elsevier, vol. 101(C).
    2. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry, 2023. "Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments," Omega, Elsevier, vol. 117(C).
    3. 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.
    4. Hosseini, Seyedmohsen & Morshedlou, Nazanin & Ivanov, Dmitry & Sarder, M.D. & Barker, Kash & Khaled, Abdullah Al, 2019. "Resilient supplier selection and optimal order allocation under disruption risks," International Journal of Production Economics, Elsevier, vol. 213(C), pages 124-137.
    5. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    6. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    7. Behzadi, Golnar & O’Sullivan, Michael Justin & Olsen, Tava Lennon & Zhang, Abraham, 2018. "Agribusiness supply chain risk management: A review of quantitative decision models," Omega, Elsevier, vol. 79(C), pages 21-42.
    8. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    9. Ghanei, Shima & Contreras, Ivan & Cordeau, Jean-François, 2023. "A two-stage stochastic collaborative intertwined supply network design problem under multiple disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    10. 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.
    11. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    12. 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.
    13. Fattahi, Mohammad, 2021. "Resilient procurement planning for supply chains: A case study for sourcing a critical mineral material," Resources Policy, Elsevier, vol. 74(C).
    14. Liu, Ming & Liu, Zhongzheng & Chu, Feng & Dolgui, Alexandre & Chu, Chengbin & Zheng, Feifeng, 2022. "An optimization approach for multi-echelon supply chain viability with disruption risk minimization," Omega, Elsevier, vol. 112(C).
    15. Nayeri, Sina & Sazvar, Zeinab & Heydari, Jafar, 2022. "A global-responsive supply chain considering sustainability and resiliency: Application in the medical devices industry," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    16. Cheramin, Meysam & Saha, Apurba Kumar & Cheng, Jianqiang & Paul, Sanjoy Kumar & Jin, Hongyue, 2021. "Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    17. Fattahi, Mohammad & Govindan, Kannan & Maihami, Reza, 2020. "Stochastic optimization of disruption-driven supply chain network design with a new resilience metric," International Journal of Production Economics, Elsevier, vol. 230(C).
    18. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2017. "Responsive contingency planning of capacitated supply networks under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 102(C), pages 13-37.
    19. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    20. 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.

    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:84:y:2019:i:c:p:232-248. 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.