Annals of Operations Research

, Volume 236, Issue 1, pp 103–129 | Cite as

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



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.


Resource allocation Risk management Oil spill  Homeland security Input–output 



Parts of this article are reprinted with the permission of the Institute of Industrial Engineers, 3577 Parkview Lane, Suite 200, Norcross, GA 30092,, Copyright@2012 by Institute of Industrial Engineers.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Cameron A. MacKenzie
    • 1
  • Hiba Baroud
    • 2
  • Kash Barker
    • 2
  1. 1.Defense Resources Management InstituteNaval Postgraduate SchoolMontereyUSA
  2. 2.School of Industrial and Systems EngineeringUniversity of OklahomaNormanUSA

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