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Modeling the effects of port disasters

Author

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  • Jomon Aliyas Paul

    (Department of Economics, Finance, & Quantitative Analysis, Kennesaw State University, 1000 Chastain Road #0403, Kennesaw, Georgia 30144, USA)

  • Michael J Maloni

    (Department of Management & Entrepreneurship, Kennesaw State University, 1000 Chastain Road #0404, Kennesaw, Georgia 30144, USA)

Abstract

Weather or terrorism-related disasters at seaports can lead to significant economic losses from vessel and cargo delays. In times of such disasters, port capacities and optimal shipment routings would change rapidly, requiring near real-time analyses for planning response operations. To address this challenge, we offer a decision support system to help port networks analyze disaster response scenarios. As part of the model, an algorithm routes arriving ships to ports to optimize the use of network capacity with respect to ocean and inland transportation, port and inventory capital costs. To reflect changing port congestion conditions, port capacities are dynamically updated in the algorithm by regression-based parametric metamodels derived from the results of a simulation model. Demonstrating application through case studies of the North American container port network, we illustrate the magnitude of cost increases from disaster-based port shutdowns and highlight the practical need for coordinated, network-wide planning for disaster response.

Suggested Citation

  • Jomon Aliyas Paul & Michael J Maloni, 2010. "Modeling the effects of port disasters," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(2), pages 127-146, June.
  • Handle: RePEc:pal:marecl:v:12:y:2010:i:2:p:127-146
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    Citations

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    Cited by:

    1. Maxim A. Dulebenets & Junayed Pasha & Olumide F. Abioye & Masoud Kavoosi, 2021. "Vessel scheduling in liner shipping: a critical literature review and future research needs," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 43-106, March.
    2. Laure Rousset & César Ducruet, 2020. "Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns," Post-Print halshs-02588551, HAL.
    3. Jasper Verschuur & Raghav Pant & Elco Koks & Jim Hall, 2022. "A systemic risk framework to improve the resilience of port and supply-chain networks to natural hazards," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 489-506, September.
    4. Asghari, Mohammad & Jaber, Mohamad Y. & Mirzapour Al-e-hashem, S.M.J., 2023. "Coordinating vessel recovery actions: Analysis of disruption management in a liner shipping service," European Journal of Operational Research, Elsevier, vol. 307(2), pages 627-644.
    5. Li, Wenjie & Asadabadi, Ali & Miller-Hooks, Elise, 2022. "Enhancing resilience through port coalitions in maritime freight networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 1-23.
    6. Laure Rousset & César Ducruet, 2020. "Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns," Networks and Spatial Economics, Springer, vol. 20(2), pages 423-447, June.
    7. Randrianarisoa, Laingo M. & Zhang, Anming, 2019. "Adaptation to climate change effects and competition between ports: Invest now or later?," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 279-322.
    8. Xueni Gou & Jasmine Siu Lee Lam, 2019. "Risk analysis of marine cargoes and major port disruptions," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(4), pages 497-523, December.
    9. Hossain, Niamat Ullah Ibne & Nur, Farjana & Hosseini, Seyedmohsen & Jaradat, Raed & Marufuzzaman, Mohammad & Puryear, Stephen M., 2019. "A Bayesian network based approach for modeling and assessing resilience: A case study of a full service deep water port," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 378-396.
    10. Panahi, Roozbeh & Ng, Adolf K.Y. & Pang, Jiayi, 2020. "Climate change adaptation in the port industry: A complex of lingering research gaps and uncertainties," Transport Policy, Elsevier, vol. 95(C), pages 10-29.
    11. Zhang, Yi & Lam, Jasmine Siu Lee, 2016. "Estimating economic losses of industry clusters due to port disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 17-33.
    12. Song, Dong-Ping & Li, Dong & Drake, Paul, 2015. "Multi-objective optimization for planning liner shipping service with uncertain port times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 1-22.
    13. Li, Chen & Qi, Xiangtong & Song, Dongping, 2016. "Real-time schedule recovery in liner shipping service with regular uncertainties and disruption events," Transportation Research Part B: Methodological, Elsevier, vol. 93(PB), pages 762-788.
    14. Olumide F. Abioye & Maxim A. Dulebenets & Junayed Pasha & Masoud Kavoosi, 2019. "A Vessel Schedule Recovery Problem at the Liner Shipping Route with Emission Control Areas," Energies, MDPI, vol. 12(12), pages 1-28, June.
    15. Pablo E. Achurra-Gonzalez & Panagiotis Angeloudis & Nils Goldbeck & Daniel J. Graham & Konstantinos Zavitsas & Marc E. J. Stettler, 2019. "Evaluation of port disruption impacts in the global liner shipping network," Journal of Shipping and Trade, Springer, vol. 4(1), pages 1-21, December.
    16. Jomon Aliyas Paul & Leo MacDonald, 2017. "An empirical analysis of US vessel-related port accidents (2002–2012): Impact of union membership and port efficiency on accident incidence and economic damage," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(4), pages 723-748, December.

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