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Importance measures for inland waterway network resilience

Author

Listed:
  • Baroud, Hiba
  • Barker, Kash
  • Ramirez-Marquez, Jose E.
  • Rocco S., Claudio M.

Abstract

This work demonstrates a time-dependent paradigm for resilience and associated stochastic metrics in a waterway transportation context. We deploy two stochastic resilience-based component importance measures that highlight the critical waterway links that contribute to waterway network resilience and develop an optimization approach that determines the order in which disrupted links should be recovered for improved resilience. A data-driven case study illustrates these metrics to describe commodity flows along the various links of the US Mississippi River Navigation System.

Suggested Citation

  • Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    • Handle: RePEc:eee:transe:v:62:y:2014:i:c:p:55-67
    DOI: 10.1016/j.tre.2013.11.010
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    1. Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Gebre, Bethel A. & Coit, David W. & Tortorella, Michael, 2006. "New insights on multi-state component criticality and importance," Reliability Engineering and System Safety, Elsevier, vol. 91(8), pages 894-904.
    2. Fumitaka Kurauchi & Nobuhiro Uno & Agachai Sumalee & Yumiko Seto, 2009. "Network Evaluation Based on Connectivity Vulnerability," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 637-649, Springer.
    3. Zhang, Pengcheng & Peeta, Srinivas, 2011. "A generalized modeling framework to analyze interdependencies among infrastructure systems," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 553-579, March.
    4. Chi Zhang & José Ramirez-Marquez & Claudio Sanseverino, 2011. "A holistic method for reliability performance assessment and critical components detection in complex networks," IISE Transactions, Taylor & Francis Journals, vol. 43(9), pages 661-675.
    5. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    6. Jonas Johansson & Henrik Hassel & Alexander Cedergren, 2011. "Vulnerability analysis of interdependent critical infrastructures: case study of the Swedish railway system," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 7(4), pages 289-316.
    7. Babcock, Michael W. & Lu, Xiaohua, 2002. "Forecasting inland waterway grain traffic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(1), pages 65-74, January.
    8. Lichun Chen & Elise Miller-Hooks, 2012. "Resilience: An Indicator of Recovery Capability in Intermodal Freight Transport," Transportation Science, INFORMS, vol. 46(1), pages 109-123, February.
    9. Cadarso, Luis & Marín, Ángel & Maróti, Gábor, 2013. "Recovery of disruptions in rapid transit networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 15-33.
    10. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    11. 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.
    12. Michael Taylor & Somenahalli Sekhar & Glen D'Este, 2006. "Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks," Networks and Spatial Economics, Springer, vol. 6(3), pages 267-291, September.
    13. Lee, Byung Kwon & Kim, Kap Hwan, 2010. "Optimizing the block size in container yards," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 120-135, January.
    14. Rocco S., Claudio M. & Emmanuel Ramirez-Marquez, José, 2013. "Identification of top contributors to system vulnerability via an ordinal optimization based method," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 92-98.
    15. Tae-Woo Lee & Nam-Kyu Park & Dong-Won Lee, 2003. "A simulation study for the logistics planning of a container terminal in view of SCM," Maritime Policy & Management, Taylor & Francis Journals, vol. 30(3), pages 243-254, July.
    16. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    17. Whitson, John C. & Ramirez-Marquez, Jose Emmanuel, 2009. "Resiliency as a component importance measure in network reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1685-1693.
    18. Rocco S., Claudio M. & Ramirez-Marquez, Jose Emmanuel, 2012. "Innovative approaches for addressing old challenges in component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 123-130.
    19. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    20. Qiang, Patrick & Nagurney, Anna, 2012. "A bi-criteria indicator to assess supply chain network performance for critical needs under capacity and demand disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 801-812.
    21. S. Sacone & S. Siri, 2009. "An integrated simulation-optimization framework for the operational planning of seaport container terminals," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 15(3), pages 275-293, January.
    22. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
    23. Zio, Enrico & Marella, Marco & Podofillini, Luca, 2007. "Importance measures-based prioritization for improving the performance of multi-state systems: application to the railway industry," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1303-1314.
    24. Zeng, Amy Z. & Durach, Christian F. & Fang, Yan, 2012. "Collaboration decisions on disruption recovery service in urban public tram systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 578-590.
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