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Optimizing the response for Arctic mass rescue events

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  • Camur, Mustafa C.
  • Sharkey, Thomas C.
  • Dorsey, Clare
  • Grabowski, Martha R.
  • Wallace, William A.

Abstract

We propose and study a model that optimizes the response to a mass rescue event in Arctic Alaska. The model contains dynamic logistics decisions for a large-scale maritime evacuation with the objectives of minimizing the impact of the event on the evacuees and the average evacuation time. Our proposed optimization model considers two interacting networks - the network that moves evacuees from the location of the event out of the Arctic (e.g., a large city in Alaska such as Anchorage) and the logistics network that moves relief materials to evacuees during the operations. We model the concept of deprivation costs by incorporating priority levels capturing the severeness of evacuees’ current medical situation and the period indicating the amount of time an evacuee has not received key relief resources. Our model is capable of understanding the best possible response given the current locations of response resources and is used to assess the effectiveness of an intuitive heuristic that mimics emergency response decision-making.

Suggested Citation

  • Camur, Mustafa C. & Sharkey, Thomas C. & Dorsey, Clare & Grabowski, Martha R. & Wallace, William A., 2021. "Optimizing the response for Arctic mass rescue events," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
  • Handle: RePEc:eee:transe:v:152:y:2021:i:c:s1366554521001368
    DOI: 10.1016/j.tre.2021.102368
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    References listed on IDEAS

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    1. 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.
    2. Stepanov, Alexander & Smith, James MacGregor, 2009. "Multi-objective evacuation routing in transportation networks," European Journal of Operational Research, Elsevier, vol. 198(2), pages 435-446, October.
    3. Yusen Ye & Wen Jiao & Hong Yan, 2020. "Managing Relief Inventories Responding to Natural Disasters: Gaps Between Practice and Literature," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 807-832, April.
    4. Li, Yuchen & Zhang, Jianghua & Yu, Guodong, 2020. "A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    5. Zhong, Shaopeng & Cheng, Rong & Jiang, Yu & Wang, Zhong & Larsen, Allan & Nielsen, Otto Anker, 2020. "Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    6. Rambha, Tarun & Nozick, Linda K. & Davidson, Rachel & Yi, Wenqi & Yang, Kun, 2021. "A stochastic optimization model for staged hospital evacuation during hurricanes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    7. Garrett, Richard A. & Sharkey, Thomas C. & Grabowski, Martha & Wallace, William A., 2017. "Dynamic resource allocation to support oil spill response planning for energy exploration in the Arctic," European Journal of Operational Research, Elsevier, vol. 257(1), pages 272-286.
    8. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
    9. Doan, Xuan Vinh & Shaw, Duncan, 2019. "Resource allocation when planning for simultaneous disasters," European Journal of Operational Research, Elsevier, vol. 274(2), pages 687-709.
    10. Lina Yu & Huasheng Yang & Lixin Miao & Canrong Zhang, 2019. "Rollout algorithms for resource allocation in humanitarian logistics," IISE Transactions, Taylor & Francis Journals, vol. 51(8), pages 887-909, August.
    11. Halit Üster & Jyotirmoy Dalal, 2017. "Strategic emergency preparedness network design integrating supply and demand sides in a multi-objective approach," IISE Transactions, Taylor & Francis Journals, vol. 49(4), pages 395-413, April.
    12. Eko Setiawan & Jiyin Liu & Alan French, 2019. "Resource location for relief distribution and victim evacuation after a sudden-onset disaster," IISE Transactions, Taylor & Francis Journals, vol. 51(8), pages 830-846, August.
    13. Shu, Jia & Lv, Wenya & Na, Qing, 2021. "Humanitarian relief supply network design: Expander graph based approach and a case study of 2013 Flood in Northeast China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    14. Sung, Inkyung & Lee, Taesik, 2016. "Optimal allocation of emergency medical resources in a mass casualty incident: Patient prioritization by column generation," European Journal of Operational Research, Elsevier, vol. 252(2), pages 623-634.
    15. Fatemeh Sabouhi & Ali Bozorgi-Amiri & Mohammad Moshref-Javadi & Mehdi Heydari, 2019. "An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study," Annals of Operations Research, Springer, vol. 283(1), pages 643-677, December.
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    1. Camur, Mustafa C. & Sharkey, Thomas C. & Vogiatzis, Chrysafis, 2023. "The stochastic pseudo-star degree centrality problem," European Journal of Operational Research, Elsevier, vol. 308(2), pages 525-539.
    2. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).

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