Emergency Planning, Hurricanes, joint location-allocation-inventory


Natural disasters, specifically hurricanes, can cause catastrophic loss of life and property. In recent years, the United States has endured significant losses due to a series of devastating hurricanes (e.g., Hurricanes Charley and Ivan in 2004, and Hurricanes Katrina and Wilma in 2005). Several Federal authorities report that there are weaknesses in the emergency and disaster planning and response models that are currently employed in practice, thus creating a need for better decision models in emergency situations. The current models not only lack fast communication with emergency responders and the public, but are also inadequate for advising the pre-positioning of supplies at emergency shelters before the storm's impact. The problem of emergency evacuation relief shelter planning during anticipated hurricane events is addressed in this research. The shelter planning problem is modeled as a joint location-allocation-inventory problem, where the number and location of shelter facilities must be identified. In addition, the evacuating citizens must be assigned to the designated shelter facilities, and the amount of emergency supply inventory to pre-position at each facility must be determined. The objective is to minimize total emergency evacuation costs, which is equal to the combined facility opening and preparation cost, evacuee transportation cost and emergency supply inventory cost. A review of the emergency evacuation planning literature reveals that this class of problems has not been largely addressed to date. First, the emergency evacuation relief sheltering problem is formulated under deterministic conditions as a mixed integer non-linear programming (MINLP) model. For three different evacuation scenarios, the proposed MINLP model yields a plan that identifies the locations of relief shelters for evacuees, the assignment of evacuees to those shelters and the amount of emergency supplies to stockpile in advance of an anticipated hurricane. The MINLP model is then used (with minor modifications) to explore the idea of equally distributing the evacuees across the open shelters. The results for the three different scenarios indicate that a balanced utilization of the open shelters is achieved with little increase in the total evacuation cost. Next, the MINLP is enhanced to consider the stochastic characteristics of both hurricane strength and projected trajectory, which can directly influence the storm's behavior. The hurricane's strength is based on its hurricane category according to the Saffir-Simpson Hurricane Scale. Its trajectory is represented as a Markov chain, where the storm's path is modeled as transitions among states (i.e., coordinate locations) within a spherical coordinate system. A specific hurricane that made landfall in the state of Florida is used as a test case for the model. Finally, the stochastic model is employed within a robust optimization strategy, where several probable hurricane behavioral scenarios are solved. Then, a single, robust evacuation sheltering plan that provides the best results, not only in terms of maximum deviation of total evacuation cost across the likely scenarios, but also in terms of maximum deviation of unmet evacuee demand at the shelter locations, is generated. The practical value of this robust plan is quite significant. This plan should accommodate unexpected changes in the behavior of an approaching storm to a reasonable degree with minimal negative impact to the total evacuation cost and the fulfillment of evacuee demand at the shelter locations. Most importantly, the re-allocation and re-mobilization of emergency personnel and supplies are not required, which can cause confusion and potentially increase the response time of responders to the hurricane emergency. The computational results show the promise of this research and usefulness of the proposed models. This work is an initial step in addressing the simultaneous identification of shelter locations, assignment of citizens to those shelters, and determination of a policy for stockpiling emergency supplies in advance of a hurricane. Both the location-allocation problem and the inventory problem have been extensively and individually studied by researchers as well as practitioners. However, this joint location-allocation-inventory problem is a difficult problem to solve, especially in the presence of stochastic storm behavior. The proposed models, even in the deterministic case, are a significant step beyond the current state-of-the-art in the area of emergency and disaster planning.


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Graduation Date





Geiger, Christopher


Doctor of Philosophy (Ph.D.)


College of Engineering and Computer Science


Industrial Engineering and Management Systems

Degree Program

Industrial Engineering








Release Date

December 2007

Length of Campus-only Access


Access Status

Doctoral Dissertation (Open Access)