IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v67y2014icp357-381.html
   My bibliography  Save this article

Dynamic and disequilibrium analysis of interdependent infrastructure systems

Author

Listed:
  • Zhang, Pengcheng
  • Peeta, Srinivas

Abstract

There is a growing awareness in recent years that the interdependencies among the civil infrastructure systems have significant economic, security and engineering implications that may influence their resiliency, efficiency and effectiveness. To capture the various types of infrastructure interdependencies and incorporate them into decision-making processes in various application domains, Zhang and Peeta (2011) propose a generalized modeling framework that combines a multilayer infrastructure network (MIN) concept and a market-based economic approach using computable general equilibrium (CGE) theory and its spatial extension (SCGE) to formulate a static equilibrium infrastructure interdependencies problem. This paper extends the framework to address the dynamic and disequilibrium aspects of the infrastructure interdependencies problems. It briefly reviews the static model, and proposes an alternative formulation for it using the variational inequality (VI) technique. Based on this equivalent VI formulation, a within-period equilibrium-tending dynamic model is proposed to illustrate how these systems evolve towards an equilibrium state within a short duration after a perturbation. To address a longer time scale, a multi-period dynamic model is proposed. This model explicitly considers the evolution of infrastructure interdependencies over time and the temporal interactions among the various systems through dynamic parameters that link the different time periods. Using this model, numerical experiments are conducted for a special case with a single region to analyze the sensitivity of the model to the various parameters, and demonstrate the ability of the modeling framework to formulate and solve practical problems such as cascading failures, disaster recovery, and budget allocation in a dynamic setting.

Suggested Citation

  • Zhang, Pengcheng & Peeta, Srinivas, 2014. "Dynamic and disequilibrium analysis of interdependent infrastructure systems," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 357-381.
  • Handle: RePEc:eee:transb:v:67:y:2014:i:c:p:357-381
    DOI: 10.1016/j.trb.2014.04.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261514000642
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.trb.2014.04.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Friesz, Terry L. & Suo, Zhong-Gui & Bernstein, David H., 1998. "A dynamic disequilibrium interregional commodity flow model," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 467-483, September.
    2. Rutherford, Thomas F, 1999. "Applied General Equilibrium Modeling with MPSGE as a GAMS Subsystem: An Overview of the Modeling Framework and Syntax," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 1-46, October.
    3. Adam Rose & Shu‐Yi Liao, 2005. "Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions," Journal of Regional Science, Wiley Blackwell, vol. 45(1), pages 75-112, February.
    4. McFarland, J. R. & Reilly, J. M. & Herzog, H. J., 2004. "Representing energy technologies in top-down economic models using bottom-up information," Energy Economics, Elsevier, vol. 26(4), pages 685-707, July.
    5. Jorgenson, Dale W. & Goettle, Richard J. & Ho, Mun S. & Wilcoxen, Peter J., 2013. "Energy, the Environment and US Economic Growth," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 477-552, Elsevier.
    6. Elias Aravantinos & Fotios Harmantzis, 2005. "A Dynamic Macroeconomic Model for the US Telecommunications Industry," Macroeconomics 0506004, University Library of Munich, Germany.
    7. Victor Ginsburgh & Michiel Keyzer, 2002. "The Structure of Applied General Equilibrium Models," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262571579, April.
    8. Daniel McFadden, 1963. "Constant Elasticity of Substitution Production Functions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 30(2), pages 73-83.
    9. Terry L. Friesz & David Bernstein & Nihal J. Mehta & Roger L. Tobin & Saiid Ganjalizadeh, 1994. "Day-To-Day Dynamic Network Disequilibria and Idealized Traveler Information Systems," Operations Research, INFORMS, vol. 42(6), pages 1120-1136, December.
    10. 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.
    11. Terry L. Friesz & David Bernstein & Roger Stough, 1996. "Dynamic Systems, Variational Inequalities and Control Theoretic Models for Predicting Time-Varying Urban Network Flows," Transportation Science, INFORMS, vol. 30(1), pages 14-31, February.
    12. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    13. Euijune Kim & Geoffrey Hewings & Chowoon Hong, 2004. "An Application of an Integrated Transport Network- Multiregional CGE Model: a Framework for the Economic Analysis of Highway Projects," Economic Systems Research, Taylor & Francis Journals, vol. 16(3), pages 235-258.
    14. James A. Giesecke & John R. Madden, 2003. "A Large†Scale Dynamic Multi†Regional Cge Model with an Illustrative Application," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 15(1), pages 02-25, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gabriel Kuper & Fabio Massacci & Woohyun Shim & Julian Williams, 2020. "Who Should Pay for Interdependent Risk? Policy Implications for Security Interdependence Among Airports," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 1001-1019, May.
    2. Zhou, Shenghua & Yang, Yifan & Ng, S. Thomas & Xu, J. Frank & Li, Dezhi, 2020. "Integrating data-driven and physics-based approaches to characterize failures of interdependent infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 31(C).
    3. Ouyang, Min & Pan, ZheZhe & Hong, Liu & He, Yue, 2015. "Vulnerability analysis of complementary transportation systems with applications to railway and airline systems in China," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 248-257.
    4. Gao, Guibing & Wang, Junshen & Yue, Wenhui & Ou, Wenchu, 2020. "Structural-vulnerability assessment of reconfigurable manufacturing system based on universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    5. Guibing, Gao & Wenhui, Yue & Wenchu, Ou & Hao, Tang, 2018. "Vulnerability evaluation method applied to manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 255-265.
    6. Lu, Qing-Chang & Xu, Peng-Cheng & Zhao, Xiangmo & Zhang, Lei & Li, Xiaoling & Cui, Xin, 2022. "Measuring network interdependency between dependent networks: A supply-demand-based approach," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    7. Suo, Weilan & Wang, Lin & Li, Jianping, 2021. "Probabilistic risk assessment for interdependent critical infrastructures: A scenario-driven dynamic stochastic model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Robson, Edward N. & Wijayaratna, Kasun P. & Dixit, Vinayak V., 2018. "A review of computable general equilibrium models for transport and their applications in appraisal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 31-53.
    3. P. Capros & Denise Van Regemorter & Leonidas Paroussos & P. Karkatsoulis & C. Fragkiadakis & S. Tsani & I. Charalampidis & Tamas Revesz, 2013. "GEM-E3 Model Documentation," JRC Research Reports JRC83177, Joint Research Centre.
    4. Giesecke, James A. & Madden, John R., 2013. "Regional Computable General Equilibrium Modeling," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 379-475, Elsevier.
    5. Jing-Li Fan & Qiao-Mei Liang & Xiao-Jie Liang & Hirokazu Tatano & Yoshio Kajitani & Yi-Ming Wei, 2014. "National vulnerability to extreme climatic events: the cases of electricity disruption in China and Japan," 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. 71(3), pages 1937-1956, April.
    6. Samiul Hasan & Greg Foliente, 2015. "Modeling infrastructure system interdependencies and socioeconomic impacts of failure in extreme events: emerging R&D challenges," 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. 78(3), pages 2143-2168, September.
    7. Chopra, Shauhrat S. & Khanna, Vikas, 2015. "Interconnectedness and interdependencies of critical infrastructures in the US economy: Implications for resilience," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 865-877.
    8. Masato Yamazaki & Atsushi Koike & Yoshinori Sone, 2018. "A Heuristic Approach to the Estimation of Key Parameters for a Monthly, Recursive, Dynamic CGE Model," Economics of Disasters and Climate Change, Springer, vol. 2(3), pages 283-301, October.
    9. Hernandez-Fajardo, Isaac & Dueñas-Osorio, Leonardo, 2013. "Probabilistic study of cascading failures in complex interdependent lifeline systems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 260-272.
    10. Wissema, Wiepke & Dellink, Rob, 2007. "AGE analysis of the impact of a carbon energy tax on the Irish economy," Ecological Economics, Elsevier, vol. 61(4), pages 671-683, March.
    11. Karplus, Valerie J. & Paltsev, Sergey & Babiker, Mustafa & Reilly, John M., 2013. "Should a vehicle fuel economy standard be combined with an economy-wide greenhouse gas emissions constraint? Implications for energy and climate policy in the United States," Energy Economics, Elsevier, vol. 36(C), pages 322-333.
    12. Liu, Huan & Tatano, Hirokazu & Pflug, Georg & Hochrainer-Stigler, Stefan, 2021. "Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    13. Euijune Kim & Geoffrey J.D. Hewings & Hidayat Amir, 2015. "Project Evaluation of Transportation Projects: an Application of Financial Computable General Equilibrium Model," ERSA conference papers ersa15p453, European Regional Science Association.
    14. Dubaniowski, Mateusz Iwo & Heinimann, Hans Rudolf, 2021. "Framework for modeling interdependencies between households, businesses, and infrastructure system, and their response to disruptions—application," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    15. Lu, Qing-Chang & Xu, Peng-Cheng & Zhao, Xiangmo & Zhang, Lei & Li, Xiaoling & Cui, Xin, 2022. "Measuring network interdependency between dependent networks: A supply-demand-based approach," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    16. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    17. Gonzalez, Mikel & Dellink, Rob B., 2006. "Impact of climate policy on the Basque country," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 6(12), pages 1-27.
    18. Otto, Vincent M. & Reilly, John, 2008. "Directed technical change and the adoption of CO2 abatement technology: The case of CO2 capture and storage," Energy Economics, Elsevier, vol. 30(6), pages 2879-2898, November.
    19. Hassan Al-Zarooni & Hamdi Bashir, 2020. "An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1204-1226, December.
    20. Rita Der Sarkissian & Chadi Abdallah & Jean-Marc Zaninetti & Sara Najem, 2020. "Modelling intra-dependencies to assess road network resilience to natural hazards," 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. 103(1), pages 121-137, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:67:y:2014:i:c:p:357-381. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.