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Prepositioning inventory for disasters: a robust and equitable model

Author

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  • German A. Velasquez

    (NC State University)

  • Maria E. Mayorga

    (NC State University)

  • Eduardo A. R. Cruz

    (Universidade Federal do Parana)

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.

Suggested Citation

  • German A. Velasquez & Maria E. Mayorga & Eduardo A. R. Cruz, 2019. "Prepositioning inventory for disasters: a robust and equitable model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 757-785, September.
  • Handle: RePEc:spr:orspec:v:41:y:2019:i:3:d:10.1007_s00291-019-00554-z
    DOI: 10.1007/s00291-019-00554-z
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    Cited by:

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    2. Wang, Jing & Cai, Jianping & Yue, Xiaohang & Suresh, Nallan C., 2021. "Pre-positioning and real-time disaster response operations: Optimization with mobile phone location data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    3. Christian Wankmüller & Gerald Reiner, 2021. "Identifying Challenges and Improvement Approaches for More Efficient Procurement Coordination in Relief Supply Chains," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    4. Yao, Chen & Fan, Bo & Zhao, Yupan & Cheng, Xinyue, 2023. "Evolutionary dynamics of supervision-compliance game on optimal pre-positioning strategies in relief supply chain management," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    5. Oscar Rodríguez-Espíndola, 2023. "Two-stage stochastic formulation for relief operations with multiple agencies in simultaneous disasters," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 477-523, June.
    6. Acar, Müge & Kaya, Onur, 2023. "Dynamic inventory decisions for humanitarian aid materials considering budget limitations," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

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