IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v236y2016i1p103-12910.1007-s10479-014-1696-1.html
   My bibliography  Save this article

Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill

Author

Listed:
  • Cameron MacKenzie
  • Hiba Baroud
  • Kash Barker

Abstract

Determining where and when to invest resources during and after a disruption can challenge policy makers and homeland security officials. Two decision models, one static and one dynamic, are proposed to determine the optimal resource allocation to facilitate the recovery of impacted industries after a disruption where the objective is to minimize the production losses due to the disruption. The paper presents necessary conditions for optimality for the static model and develops an algorithm that finds every possible solution that satisfies those necessary conditions. A deterministic branch-and-bound algorithm solves the dynamic model and relies on a convex relaxation of the dynamic optimization problem. Both models are applied to the Deepwater Horizon oil spill, which adversely impacted several industries in the Gulf region, such as fishing, tourism, real estate, and oil and gas. Results demonstrate the importance of allocating enough resources to stop the oil spill and clean up the oil, which reduces the economic loss across all industries. These models can be applied to different homeland security and disaster response situations to help governments and organizations decide among different resource allocation strategies during and after a disruption. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • Cameron MacKenzie & Hiba Baroud & Kash Barker, 2016. "Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill," Annals of Operations Research, Springer, vol. 236(1), pages 103-129, January.
    • Handle: RePEc:spr:annopr:v:236:y:2016:i:1:p:103-129:10.1007/s10479-014-1696-1
    DOI: 10.1007/s10479-014-1696-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-014-1696-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-014-1696-1?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. Aldy, Joseph Edgar, 2011. "Real-Time Economic Analysis and Policy Development During the BP Deepwater Horizon Oil Spill," Scholarly Articles 5241379, Harvard Kennedy School of Government.
    2. Jun Zhuang & Vicki M. Bier, 2007. "Balancing Terrorism and Natural Disasters---Defensive Strategy with Endogenous Attacker Effort," Operations Research, INFORMS, vol. 55(5), pages 976-991, October.
    3. Harilaos N. Psaraftis & Babis O. Ziogas, 1985. "A Tactical Decision Algorithm for the Optimal Dispatching of Oil Spill Cleanup Equipment," Management Science, INFORMS, vol. 31(12), pages 1475-1491, December.
    4. Niyazi Bakır, 2011. "A Stackelberg game model for resource allocation in cargo container security," Annals of Operations Research, Springer, vol. 187(1), pages 5-22, July.
    5. Nada Petrovic & David L Alderson & Jean M Carlson, 2012. "Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-9, April.
    6. W. E. Wilhelm & A. V. Srinivasa, 1997. "Prescribing Tactical Response for Oil Spill Clean Up Operations," Management Science, INFORMS, vol. 43(3), pages 386-402, March.
    7. Paolo Dell'Olmo & Guglielmo Lulli, 2004. "Planning Activities in a Network of Logistic Platforms with Shared Resources," Annals of Operations Research, Springer, vol. 129(1), pages 155-169, July.
    8. May Cheung & Jun Zhuang, 2012. "Regulation Games Between Government and Competing Companies: Oil Spills and Other Disasters," Decision Analysis, INFORMS, vol. 9(2), pages 156-164, June.
    9. Hausken, Kjell & Zhuang, Jun, 2013. "The impact of disaster on the strategic interaction between company and government," European Journal of Operational Research, Elsevier, vol. 225(2), pages 363-376.
    10. Robin L. Dillon & M. Elisabeth Paté-Cornell & Seth D. Guikema, 2003. "Programmatic Risk Analysis for Critical Engineering Systems Under Tight Resource Constraints," Operations Research, INFORMS, vol. 51(3), pages 354-370, June.
    11. Xiaojun Shan & Jun Zhuang, 2013. "Cost of Equity in Homeland Security Resource Allocation in the Face of a Strategic Attacker," Risk Analysis, John Wiley & Sons, vol. 33(6), pages 1083-1099, June.
    12. Vicki M. Bier, 2007. "Choosing What to Protect," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 607-620, June.
    13. E. L. Lawler & D. E. Wood, 1966. "Branch-and-Bound Methods: A Survey," Operations Research, INFORMS, vol. 14(4), pages 699-719, August.
    14. Peter Gordon & James E. Moore II & Harry W. Richardson & Qisheng Pan, 2005. "The Economic Impact of a Terrorist Attack on the Twin Ports of Los Angeles–Long Beach," Chapters, in: Harry W. Richardson & Peter Gordon & James E. Moore II (ed.), The Economic Impacts of Terrorist Attacks, chapter 14, Edward Elgar Publishing.
    15. Richards, Timothy J. & Patterson, Paul M., 1999. "The Economic Value Of Public Relations Expenditures: Food Safety And The Strawberry Case," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(2), pages 1-23, December.
    16. 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.
    17. Henry H. Willis, 2007. "Guiding Resource Allocations Based on Terrorism Risk," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 597-606, June.
    18. 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.
    19. Verbeke, Wim & Ward, Ronald W., 2001. "A fresh meat almost ideal demand system incorporating negative TV press and advertising impact," Agricultural Economics, Blackwell, vol. 25(2-3), pages 359-374, September.
    20. Crowther, Kenneth G., 2008. "Decentralized risk management for strategic preparedness of critical infrastructure through decomposition of the inoperability input–output model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 1(C), pages 53-67.
    21. Kash Barker & Joost R. Santos, 2010. "A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems," Risk Analysis, John Wiley & Sons, vol. 30(6), pages 962-974, June.
    22. Richard Daniels & Barbara Hoopes & Joseph Mazzola, 1997. "An analysis of heuristics for the parallel-machine flexible-resource scheduling problem," Annals of Operations Research, Springer, vol. 70(0), pages 439-472, April.
    23. Srinivasa, Anand V. & Wilhelm, Wilbert E., 1997. "A procedure for optimizing tactical response in oil spill clean up operations," European Journal of Operational Research, Elsevier, vol. 102(3), pages 554-574, November.
    24. Shan, Xiaojun & Zhuang, Jun, 2013. "Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender–attacker game," European Journal of Operational Research, Elsevier, vol. 228(1), pages 262-272.
    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. Chao Zhang & Jingjing Kong & Slobodan P Simonovic, 2018. "Modeling joint restoration strategies for interdependent infrastructure systems," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-18, April.
    2. Talebiyan, Hesam & Dueñas-Osorio, Leonardo, 2023. "Auctions for resource allocation and decentralized restoration of interdependent networks," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Rui Peng & Di Wu & Mengyao Sun & Shaomin Wu, 2021. "An attack-defense game on interdependent networks," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(10), pages 2331-2341, October.
    4. Magoua, Joseph Jonathan & Li, Nan, 2023. "The human factor in the disaster resilience modeling of critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    5. Jingjing Kong & Chao Zhang & Slobodan P. Simonovic, 2019. "A Two-Stage Restoration Resource Allocation Model for Enhancing the Resilience of Interdependent Infrastructure Systems," Sustainability, MDPI, vol. 11(19), pages 1-16, September.
    6. Doan, Xuan Vinh & Shaw, Duncan, 2019. "Resource allocation when planning for simultaneous disasters," European Journal of Operational Research, Elsevier, vol. 274(2), pages 687-709.

    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. Cameron A. MacKenzie & Hiba Baroud & Kash Barker, 2016. "Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill," Annals of Operations Research, Springer, vol. 236(1), pages 103-129, January.
    2. Talarico, Luca & Reniers, Genserik & Sörensen, Kenneth & Springael, Johan, 2015. "MISTRAL: A game-theoretical model to allocate security measures in a multi-modal chemical transportation network with adaptive adversaries," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 105-114.
    3. Simon, Jay & Omar, Ayman, 2020. "Cybersecurity investments in the supply chain: Coordination and a strategic attacker," European Journal of Operational Research, Elsevier, vol. 282(1), pages 161-171.
    4. Zhang, Jing & Zhuang, Jun, 2019. "Modeling a multi-target attacker-defender game with multiple attack types," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 465-475.
    5. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    6. Adam Behrendt & Vineet M. Payyappalli & Jun Zhuang, 2019. "Modeling the Cost Effectiveness of Fire Protection Resource Allocation in the United States: Models and a 1980–2014 Case Study," Risk Analysis, John Wiley & Sons, vol. 39(6), pages 1358-1381, June.
    7. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    8. Peiqiu Guan & Jun Zhuang, 2016. "Modeling Resources Allocation in Attacker‐Defender Games with “Warm Up” CSF," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 776-791, April.
    9. Jie Xu & Jun Zhuang, 2016. "Modeling costly learning and counter-learning in a defender-attacker game with private defender information," Annals of Operations Research, Springer, vol. 236(1), pages 271-289, January.
    10. Qingqing Zhai & Rui Peng & Jun Zhuang, 2020. "Defender–Attacker Games with Asymmetric Player Utilities," Risk Analysis, John Wiley & Sons, vol. 40(2), pages 408-420, February.
    11. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    12. Yacov Y. Haimes & Kenneth Crowther & Barry M. Horowitz, 2008. "Homeland security preparedness: Balancing protection with resilience in emergent systems," Systems Engineering, John Wiley & Sons, vol. 11(4), pages 287-308, December.
    13. Daniel Seaberg & Laura Devine & Jun Zhuang, 2017. "A review of game theory applications in natural disaster management research," 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. 89(3), pages 1461-1483, December.
    14. Kjell Hausken & Jun Zhuang, 2016. "The strategic interaction between a company and the government surrounding disasters," Annals of Operations Research, Springer, vol. 237(1), pages 27-40, February.
    15. Nageswara S. V. Rao & Stephen W. Poole & Chris Y. T. Ma & Fei He & Jun Zhuang & David K. Y. Yau, 2016. "Defense of Cyber Infrastructures Against Cyber‐Physical Attacks Using Game‐Theoretic Models," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 694-710, April.
    16. Pourakbar, M. & Zuidwijk, R.A., 2018. "The role of customs in securing containerized global supply chains," European Journal of Operational Research, Elsevier, vol. 271(1), pages 331-340.
    17. Bose, Gautam & Konrad, Kai A., 2020. "Devil take the hindmost: Deflecting attacks to other defenders," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    18. Mohammad E. Nikoofal & Mehmet Gümüs, 2015. "On the value of terrorist’s private information in a government’s defensive resource allocation problem," IISE Transactions, Taylor & Francis Journals, vol. 47(6), pages 533-555, June.
    19. Hunt, Kyle & Zhuang, Jun, 2024. "A review of attacker-defender games: Current state and paths forward," European Journal of Operational Research, Elsevier, vol. 313(2), pages 401-417.
    20. Jie Xu & Jun Zhuang & Zigeng Liu, 2016. "Modeling and mitigating the effects of supply chain disruption in a defender–attacker game," Annals of Operations Research, Springer, vol. 236(1), pages 255-270, January.

    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:spr:annopr:v:236:y:2016:i:1:p:103-129:10.1007/s10479-014-1696-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.