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Optimal supply chain resilience with consideration of failure propagation and repair logistics

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  • Goldbeck, Nils
  • Angeloudis, Panagiotis
  • Ochieng, Washington

Abstract

The joint optimisation of investments in capacity and repair capability of production and logistics systems at risk of being damaged is an important aspect of supply chain resilience that is not sufficiently addressed by state-of-the-art modelling approaches. Furthermore, logistical issues of procuring repair resources impact speed of recovery but are not considered in most existing models. This paper presents a novel multi-stage stochastic programming model that optimizes pre-disruption investment decisions, as well as post-disruption dynamic adjustment of supply chain operations and allocation of repair resources. A case study demonstrates how the method can quantify the effects of pooling repair resources.

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  • Goldbeck, Nils & Angeloudis, Panagiotis & Ochieng, Washington, 2020. "Optimal supply chain resilience with consideration of failure propagation and repair logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    • Handle: RePEc:eee:transe:v:133:y:2020:i:c:s1366554519302406
    DOI: 10.1016/j.tre.2019.101830
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    1. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2016. "A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 116-133.
    2. Fahimnia, Behnam & Jabbarzadeh, Armin & Sarkis, Joseph, 2018. "Greening versus resilience: A supply chain design perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 129-148.
    3. Lam, Jasmine Siu Lee & Bai, Xiwen, 2016. "A quality function deployment approach to improve maritime supply chain resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 92(C), pages 16-27.
    4. Fahimnia, Behnam & Jabbarzadeh, Armin, 2016. "Marrying supply chain sustainability and resilience: A match made in heaven," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 306-324.
    5. Sean P. Willems, 2008. "Data Set--Real-World Multiechelon Supply Chains Used for Inventory Optimization," Manufacturing & Service Operations Management, INFORMS, vol. 10(1), pages 19-23, February.
    6. Ghavamifar, Ali & Makui, Ahmad & Taleizadeh, Ata Allah, 2018. "Designing a resilient competitive supply chain network under disruption risks: A real-world application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 87-109.
    7. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    8. Silke Friedrich, 2013. "Energy Efficiency in Buildings in EU Countries," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 11(2), pages 57-59, 07.
    9. Chen, Li-Ming & Liu, Yan Emma & Yang, Shu-Jung Sunny, 2015. "Robust supply chain strategies for recovering from unanticipated disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 198-214.
    10. Oecd, 2013. "Building Blocks for Smart Networks," OECD Digital Economy Papers 215, OECD Publishing.
    11. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    12. Azaron, A. & Brown, K.N. & Tarim, S.A. & Modarres, M., 2008. "A multi-objective stochastic programming approach for supply chain design considering risk," International Journal of Production Economics, Elsevier, vol. 116(1), pages 129-138, November.
    13. 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.
    14. 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.
    15. Salehi Sadghiani, N. & Torabi, S.A. & Sahebjamnia, N., 2015. "Retail supply chain network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 95-114.
    16. Kök, A. Gürhan & Shang, Kevin H., 2014. "Evaluation of cycle-count policies for supply chains with inventory inaccuracy and implications on RFID investments," European Journal of Operational Research, Elsevier, vol. 237(1), pages 91-105.
    17. Li, Xiaopeng & Ouyang, Yanfeng & Peng, Fan, 2013. "A supporting station model for reliable infrastructure location design under interdependent disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 80-93.
    18. Nurre, Sarah G. & Cavdaroglu, Burak & Mitchell, John E. & Sharkey, Thomas C. & Wallace, William A., 2012. "Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem," European Journal of Operational Research, Elsevier, vol. 223(3), pages 794-806.
    19. William Ho & Tian Zheng & Hakan Yildiz & Srinivas Talluri, 2015. "Supply chain risk management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 5031-5069, August.
    20. Hou, Yunzhang & Wang, Xiaoling & Wu, Yenchun Jim & He, Peixu, 2018. "How does the trust affect the topology of supply chain network and its resilience? An agent-based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 229-241.
    21. Salal Humair & John D. Ruark & Brian Tomlin & Sean P. Willems, 2013. "Incorporating Stochastic Lead Times Into the Guaranteed Service Model of Safety Stock Optimization," Interfaces, INFORMS, vol. 43(5), pages 421-434, October.
    22. Fang Liu & Jing-Sheng Song & Jordan D. Tong, 2016. "Building Supply Chain Resilience through Virtual Stockpile Pooling," Production and Operations Management, Production and Operations Management Society, vol. 25(10), pages 1745-1762, October.
    23. Hosseini, Seyedmohsen & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "A review of definitions and measures of system resilience," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 47-61.
    24. 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.
    25. Helfgott, Ariella, 2018. "Operationalising systemic resilience," European Journal of Operational Research, Elsevier, vol. 268(3), pages 852-864.
    26. Gillen, David & Hasheminia, Hamed, 2016. "Measuring reliability of transportation networks using snapshots of movements in the network – An analytical and empirical study," Transportation Research Part B: Methodological, Elsevier, vol. 93(PB), pages 808-824.
    27. repec:ces:ifodic:v:11:y:2013:i:2:p:19094737 is not listed on IDEAS
    28. Masih-Tehrani, Behdad & Xu, Susan H. & Kumara, Soundar & Li, Haijun, 2011. "A single-period analysis of a two-echelon inventory system with dependent supply uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1128-1151, September.
    29. ., 2013. "The evolution of mutual building societies," Chapters, in: Finance in an Age of Austerity, chapter 4, pages 64-87, Edward Elgar Publishing.
    30. Pant, Raghav & Barker, Kash & Zobel, Christopher W., 2014. "Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 92-102.
    31. Barker, Kash & Santos, Joost R., 2010. "Measuring the efficacy of inventory with a dynamic input-output model," International Journal of Production Economics, Elsevier, vol. 126(1), pages 130-143, July.
    32. Khaled, Abdullah A. & Jin, Mingzhou & Clarke, David B. & Hoque, Mohammad A., 2015. "Train design and routing optimization for evaluating criticality of freight railroad infrastructures," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 71-84.
    33. Gregory D. Glockner & George L. Nemhauser, 2000. "A Dynamic Network Flow Problem with Uncertain arc Capacities: Formulation and Problem Structure," Operations Research, INFORMS, vol. 48(2), pages 233-242, April.
    34. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    35. Lu, Mengshi & Huang, Simin & Shen, Zuo-Jun Max, 2011. "Product substitution and dual sourcing under random supply failures," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1251-1265, September.
    36. Rezapour, Shabnam & Allen, Janet K. & Mistree, Farrokh, 2015. "Uncertainty propagation in a supply chain or supply network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 185-206.
    37. Pant, Raghav & Barker, Kash & Grant, F. Hank & Landers, Thomas L., 2011. "Interdependent impacts of inoperability at multi-modal transportation container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(5), pages 722-737, September.
    38. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.
    39. Zhalechian, M. & Torabi, S. Ali & Mohammadi, M., 2018. "Hub-and-spoke network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 20-43.
    40. Cui, Jianxun & Zhao, Meng & Li, Xiaopeng & Parsafard, Mohsen & An, Shi, 2016. "Reliable design of an integrated supply chain with expedited shipments under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 143-163.
    41. Wilson, Martha C., 2007. "The impact of transportation disruptions on supply chain performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 295-320, July.
    42. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    43. Joost R. Santos & Yacov Y. Haimes, 2004. "Modeling the Demand Reduction Input‐Output (I‐O) Inoperability Due to Terrorism of Interconnected Infrastructures," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1437-1451, December.
    44. Chen, Hong & Cullinane, Kevin & Liu, Nan, 2017. "Developing a model for measuring the resilience of a port-hinterland container transportation network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 282-301.
    45. Benjamin R. Tukamuhabwa & Mark Stevenson & Jerry Busby & Marta Zorzini, 2015. "Supply chain resilience: definition, review and theoretical foundations for further study," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5592-5623, September.
    46. Jabbarzadeh, Armin & Fahimnia, Behnam & Sheu, Jiuh-Biing & Moghadam, Hani Shahmoradi, 2016. "Designing a supply chain resilient to major disruptions and supply/demand interruptions," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 121-149.
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