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. This is the author’s accepted manuscript to appear in the Annals of Operations Research. The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-014-1696-1. Portions of this work appeared as a conference paper for the Industrial and Systems Engineering Research Conference. Those portions are reprinted with the permission of the Institute of Industrial Engineers, 3577 Parkway Lane, Suite 200, Norcorss, GA 30092, www.iienet.org, Copyright@2012 by Institute of Industrial Engineers. This work was funded in part by the National Science Foundation, Division of Civil, Mechanical, and Manufacturing Innovation, under award 0927299. C. A. MacKenzie Defense Resources Management Institute, Naval Postgraduate School, Monterey, CA 93943 Tel.: 831-656-2224 E-mail: [email protected] H. Baroud School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73019 E-mail: [email protected] K. Barker School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73019 E-mail: [email protected]