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Prepositioning inventory for disasters: a robust and equitable model

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Abstract

Disaster responses are usually joint efforts between agencies of different sizes and specialties. Improving disaster response can be achieved by prepositioning relief items in the appropriate amount and at the appropriate locations. In this paper, we develop a multi-agency prepositioning model under uncertainty. In particular, we develop a model in which the prepositioning strategy developed by a major aid agency or a local government considers sharing resources with other aid agencies. The proposed model considers multiple relief item types, storage capacity, budgetary and equity constraints while integrating supplier selection, inventory and facility location decisions. Uncertainty is modeled using robust optimization. We provide a deterministic model as well as its robust counterpart where demand and link disruptions are considered uncertain. In addition, a heuristic approach for solving the uncapacitated deterministic version of the proposed model is provided. In order to evaluate the proposed model and heuristic, two computational experiments are presented. In the first experiment, we assess the quality of the robust solutions by simulating a number of realizations. In the second experiment, we test the performance of the heuristic compared to the optimal policy.

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Acknowledgements

We would like to thank Dr. Julie Casani, former Director of Public Health Preparedness for the state of North Carolina and Adjunct Associate Professor of Biological Sciences at NC State University and Dr. Michael Kay, Associate Professor at NC State University, for their valuable suggestions.

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Correspondence to German A. Velasquez.

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Velasquez, G.A., Mayorga, M.E. & Cruz, E.A.R. Prepositioning inventory for disasters: a robust and equitable model. OR Spectrum 41, 757–785 (2019). https://doi.org/10.1007/s00291-019-00554-z

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