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Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study

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  • Sawik, Tadeusz

Abstract

This paper presents a multi-portfolio approach and scenario-based stochastic MIP (mixed integer programming) models for optimization of supply chain operations under ripple effect. The ripple effect is caused by regional pandemic disruption risks propagated from a single primary source region and triggering delayed regional disruptions of different durations in other regions. The propagated regional disruption risks are assumed to impact both primary and backup suppliers of parts, OEM (Original Equipment Manufacturer) assembly plants as well as market demand. As a result, simultaneous disruptions in supply, demand and logistics across the entire supply chain is observed. The mitigation and recovery decisions made to improve the supply chain resilience include pre-positioning of RMI (Risk Mitigation Inventory) of parts at OEM plants and ordering recovery supplies from backup suppliers of parts, located outside the primary source region. The decisions are spatiotemporally integrated. The pre-positioning of RMI implemented before a disruptive event is optimized simultaneously with the RMI usage and recovery supply portfolios for the backup suppliers in the aftermath periods. The recovery supplies of parts and production at OEM plants, are coordinated under random availability of suppliers and plants and random market demand. The resilient solutions for the resilient supply portfolios are compared with the non-resilient solutions with no recovery resources available. The findings indicate that the resilient measures commonly used to mitigate the impacts of region-specific disruptions can be successfully applied for mitigation the impacts of multi-regional pandemic disruptions and the ripple effect.

Suggested Citation

  • Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:jomega:v:109:y:2022:i:c:s0305048322000056
    DOI: 10.1016/j.omega.2022.102596
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    References listed on IDEAS

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    1. Florian Lücker & Ralf W. Seifert & Işık Biçer, 2019. "Roles of inventory and reserve capacity in mitigating supply chain disruption risk," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1238-1249, February.
    2. Deepa Mishra & Yogesh K. Dwivedi & Nripendra P. Rana & Elkafi Hassini, 2021. "Evolution of supply chain ripple effect: a bibliometric and meta-analytic view of the constructs," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 129-147, January.
    3. Sawik, Tadeusz, 2021. "On the risk-averse selection of resilient multi-tier supply portfolio," Omega, Elsevier, vol. 101(C).
    4. 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.
    5. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    6. 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.
    7. Cavalcante, Ian M. & Frazzon, Enzo M. & Forcellini, Fernando A. & Ivanov, Dmitry, 2019. "A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing," International Journal of Information Management, Elsevier, vol. 49(C), pages 86-97.
    8. Dmitry Ivanov, 2021. "Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 59(12), pages 3535-3552, June.
    9. Zhimei Lei & Ming K. Lim & Li Cui & Yanzhang Wang, 2021. "Modelling of risk transmission and control strategy in the transnational supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 148-167, January.
    10. 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.
    11. 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.
    12. 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).
    13. Ming Liu & Zhongzheng Liu & Feng Chu & Feifeng Zheng & Chengbin Chu, 2021. "A new robust dynamic Bayesian network approach for disruption risk assessment under the supply chain ripple effect," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 265-285, January.
    14. Alexandre Dolgui & Dmitry Ivanov, 2021. "Ripple effect and supply chain disruption management: new trends and research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 102-109, January.
    15. Tadeusz Sawik, 2020. "Selection of Resilient Multi-Tier Supply Portfolio: A Two-Period Approach," International Series in Operations Research & Management Science, in: Supply Chain Disruption Management, edition 2, chapter 0, pages 401-423, Springer.
    16. Tadeusz Sawik, 2020. "Selection of Resilient Multi-Tier Supply Portfolio," International Series in Operations Research & Management Science, in: Supply Chain Disruption Management, edition 2, chapter 0, pages 367-400, Springer.
    17. 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).
    18. Tadeusz Sawik, 2020. "Supply Chain Disruption Management," International Series in Operations Research and Management Science, Springer, edition 2, number 978-3-030-44814-1, December.
    19. He, Jian & Alavifard, Farzad & Ivanov, Dmitry & Jahani, Hamed, 2019. "A real-option approach to mitigate disruption risk in the supply chain," Omega, Elsevier, vol. 88(C), pages 133-149.
    20. Girol Karacaoglu & Jacek B. Krawczyk, 2021. "Public policy, systemic resilience and viability theory," Metroeconomica, Wiley Blackwell, vol. 72(4), pages 826-848, November.
    21. Tadeusz Sawik, 2016. "On the risk-averse optimization of service level in a supply chain under disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 98-113, January.
    22. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    23. Sanjoy Kumar Paul & Priyabrata Chowdhury, 2020. "Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(3), pages 283-293, September.
    24. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    25. Tadeusz Sawik, 2020. "Selection of Dynamic Supply Portfolio," International Series in Operations Research & Management Science, in: Supply Chain Disruption Management, edition 2, chapter 0, pages 47-75, Springer.
    26. Sawik, Tadeusz, 2019. "Disruption mitigation and recovery in supply chains using portfolio approach," Omega, Elsevier, vol. 84(C), pages 232-248.
    27. Dmitry Ivanov, 2018. "Structural Dynamics and Resilience in Supply Chain Risk Management," International Series in Operations Research and Management Science, Springer, number 978-3-319-69305-7, December.
    28. Tadeusz Sawik, 2020. "Selection of Resilient Supply Portfolio," International Series in Operations Research & Management Science, in: Supply Chain Disruption Management, edition 2, chapter 0, pages 77-108, Springer.
    29. Dmitry Ivanov & Alexandre Dolgui, 2020. "Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2904-2915, May.
    30. Sanjay Mehrotra & Hamed Rahimian & Masoud Barah & Fengqiao Luo & Karolina Schantz, 2020. "A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(5), pages 303-320, August.
    31. Seyed Mohammad Gholami-Zanjani & Mohammad Saeed Jabalameli & Walid Klibi & Mir Saman Pishvaee, 2021. "A robust location-inventory model for food supply chains operating under disruptions with ripple effects," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 301-324, January.
    32. 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.
    33. 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.
    34. Jafar Namdar & Xueping Li & Rupy Sawhney & Ninad Pradhan, 2018. "Supply chain resilience for single and multiple sourcing in the presence of disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2339-2360, March.
    35. Tadeusz Sawik, 2020. "A two-period model for selection of resilient multi-tier supply portfolio," International Journal of Production Research, Taylor & Francis Journals, vol. 58(19), pages 6043-6060, October.
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