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Optimal location, capacity and timing of stockpiles for improved hurricane preparedness

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  • Paul, Jomon Aliyas
  • MacDonald, Leo

Abstract

Applying historical hurricane data to model storm related uncertainty, this paper develops a stochastic optimization model to determine the stockpile location and capacities of medical supplies for improved disaster preparedness in the event of a hurricane. Our models incorporate facility damage and casualty losses, based upon their severity levels and remaining survivability time, as a function of time variant changes in hurricane conditions. To determine the optimal deployment time, we use an optimal stopping time framework to model the trade-offs between increasing costs and reduced uncertainty as the hurricane approaches landfall. Finally, aided by an innovative mixed integer programming model, we develop an evolutionary optimization heuristic that yields time efficient high quality solutions for solving large-scale problems, then demonstrate the applicability of the approach via illustrative numeric examples.

Suggested Citation

  • Paul, Jomon Aliyas & MacDonald, Leo, 2016. "Optimal location, capacity and timing of stockpiles for improved hurricane preparedness," International Journal of Production Economics, Elsevier, vol. 174(C), pages 11-28.
  • Handle: RePEc:eee:proeco:v:174:y:2016:i:c:p:11-28
    DOI: 10.1016/j.ijpe.2016.01.006
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    2. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    3. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    4. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    5. Eghbal Akhlaghi, Vahid & Campbell, Ann Melissa & de Matta, Renato E., 2021. "Fuel distribution planning for disasters: Models and case study for Puerto Rico," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    6. Hanif Malekpoor & Konstantinos Chalvatzis & Nishikant Mishra & Amar Ramudhin, 2019. "A hybrid approach of VIKOR and bi-objective integer linear programming for electrification planning in a disaster relief camp," Annals of Operations Research, Springer, vol. 283(1), pages 443-469, December.
    7. Hu, Shaolong & Dong, Zhijie Sasha & Lev, Benjamin, 2022. "Supplier selection in disaster operations management: Review and research gap identification," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    8. Sachin Modgil & Rohit Kumar Singh & Cyril Foropon, 2022. "Quality management in humanitarian operations and disaster relief management: a review and future research directions," Annals of Operations Research, Springer, vol. 319(1), pages 1045-1098, December.
    9. Fang Xu & Yifan Ma & Chang Liu & Ying Ji, 2024. "Emergency Logistics Facilities Location Dual-Objective Modeling in Uncertain Environments," Sustainability, MDPI, vol. 16(4), pages 1-34, February.
    10. Paul, Jomon A. & Zhang, Minjiao, 2019. "Supply location and transportation planning for hurricanes: A two-stage stochastic programming framework," European Journal of Operational Research, Elsevier, vol. 274(1), pages 108-125.

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