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Locating Backup Facilities to Enhance Supply Chain Disaster Resilience

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  • SAMUEL RATICK
  • BRIAN MEACHAM
  • YUKO AOYAMA

Abstract

The use of emergency backup and storage facilities to supplement existing facilities in response to the potential effects of various natural and anthropogenic hazards (e.g., floods, fires, outages, and acts of malice) can be an effective way of reducing vulnerability and enhancing the resilience of supply chain and other logistics functions. Although there can be additional costs associated with utilizing emergency backup and storage facilities, they can be a particularly attractive and cost‐effective alternative in those cases where long‐term disruptions can, or should, be expected. In this paper we use set cover location modeling as a decision to determine the number of backup facilities to locate under varying cover, anticover, and complementary anticover distances. We then add the flexibility of allowing existing facilities to serve as backup facilities and explore the interrelationships among hazards, vulnerability, and location. Finally, these model formulations are applied to an example data set over 900 cities and towns in New England and New York.

Suggested Citation

  • Samuel Ratick & Brian Meacham & Yuko Aoyama, 2008. "Locating Backup Facilities to Enhance Supply Chain Disaster Resilience," Growth and Change, Wiley Blackwell, vol. 39(4), pages 642-666, December.
  • Handle: RePEc:bla:growch:v:39:y:2008:i:4:p:642-666
    DOI: 10.1111/j.1468-2257.2008.00450.x
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    Cited by:

    1. Yi Zheng & Li Liu & Victor Shi & Wenxing Huang & Jianxiu Liao, 2022. "A Resilience Analysis of a Medical Mask Supply Chain during the COVID-19 Pandemic: A Simulation Modeling Approach," IJERPH, MDPI, vol. 19(13), pages 1-21, June.
    2. 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.
    3. Jia, Chuanzhou & Zhang, Chi & Li, Yan-Fu & Li, Quan-Lin, 2023. "Joint pre- and post-disaster planning to enhance the resilience of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    4. Shashi & Piera Centobelli & Roberto Cerchione & Myriam Ertz, 2020. "Managing supply chain resilience to pursue business and environmental strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1215-1246, March.
    5. Rajak, Sonu & Mathiyazhagan, K. & Agarwal, Vernika & Sivakumar, K. & Kumar, Vikas & Appolloni, Andrea, 2022. "Issues and analysis of critical success factors for the sustainable initiatives in the supply chain during COVID- 19 pandemic outbreak in India: A case study," Research in Transportation Economics, Elsevier, vol. 93(C).
    6. Sam Ratick & Jeffrey Osleeb & Kangping Si, 2016. "The Maximal Cover Location Model with Hedging," International Regional Science Review, , vol. 39(1), pages 77-107, January.
    7. Liu, Chiung-Lin & Shang, Kuo-Chung & Lirn, Taih-Cherng & Lai, Kee-Hung & Lun, Y.H. Venus, 2018. "Supply chain resilience, firm performance, and management policies in the liner shipping industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 202-219.
    8. Harpreet Kaur & Surya Prakash Singh, 2019. "Sustainable procurement and logistics for disaster resilient supply chain," Annals of Operations Research, Springer, vol. 283(1), pages 309-354, December.
    9. Sahitya Elluru & Hardik Gupta & Harpreet Kaur & Surya Prakash Singh, 2019. "Proactive and reactive models for disaster resilient supply chain," Annals of Operations Research, Springer, vol. 283(1), pages 199-224, December.
    10. Annarelli, Alessandro & Nonino, Fabio, 2016. "Strategic and operational management of organizational resilience: Current state of research and future directions," Omega, Elsevier, vol. 62(C), pages 1-18.
    11. Gilani Larimi, Niloofar & Azhdari, Abolghasem & Ghousi, Rouzbeh & Du, Bo, 2022. "Integrating GIS in reorganizing blood supply network in a robust-stochastic approach by combating disruption damages," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    12. Margolis, Joshua T. & Sullivan, Kelly M. & Mason, Scott J. & Magagnotti, Mariah, 2018. "A multi-objective optimization model for designing resilient supply chain networks," International Journal of Production Economics, Elsevier, vol. 204(C), pages 174-185.
    13. Reza Yazdanparast & Reza Tavakkoli-Moghaddam & Razieh Heidari & Leyla Aliabadi, 2021. "A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 611-631, June.
    14. Wang, Mengyue & Huang, Hongxuan, 2019. "The design of a flexible capital-constrained global supply chain by integrating operational and financial strategies," Omega, Elsevier, vol. 88(C), pages 40-62.
    15. Mark Horner & Michael Widener, 2011. "The effects of transportation network failure on people’s accessibility to hurricane disaster relief goods: a modeling approach and application to a Florida case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 59(3), pages 1619-1634, December.

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