Abstract
Pre-positioning and distribution of emergency supplies are important activities in the preparedness and response stages for disasters. The goal of this paper is to address the joint decision-making of pre-positioning and distribution of relief supplies under uncertain environment. A two-stage stochastic programming model with the objective of the minimizing total cost is formulated and the uncertainties of disasters are taken into account. A case study focusing on addressing hurricane threats in the Gulf Coast area of the US is conducted to illustrated the application of the proposed model. The results analysis provides managerial insights for relief agencies.
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References
Boonmee, C., Arimura, M., Asada, T.: Facility location optimization model for emergency humanitarian logistics. Int. J. Disaster Risk Reduct. 24, 485–498 (2017)
Chang, M.S., Tseng, Y.L., Chen, J.W.: A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transp. Res. Part E Logist. Transp. Rev. 43(6), 737–754 (2007)
Chen, J., Liang, L., Yao, D.Q.: Pre-positioning of relief inventories for non-profit organizations: a newsvendor approach. Ann. Oper. Res. 259(1–2), 35–63 (2017)
Duran, S., Gutierrez, M.A., Keskinocak, P.: Pre-positioning of emergency items for care international. Interfaces 41(3), 223–237 (2011)
Galindo, G., Batta, R.: Prepositioning of supplies in preparation for a hurricane under potential destruction of prepositioned supplies. Socio Econ. Plan. Sci. 47(1), 20–37 (2013)
Hu, S., Dong, Z.S.: Supplier selection and pre-positioning strategy in humanitarian relief. Omega 83, 287–298 (2019)
Hu, S.L., Han, C.F., Meng, L.P.: Stochastic optimization for joint decision making of inventory and procurement in humanitarian relief. Comput. Ind. Eng. 111, 39–49 (2017)
Mete, H.O., Zabinsky, Z.B.: Stochastic optimization of medical supply location and distribution in disaster management. Int. J. Prod. Econ. 126(1), 76–84 (2010)
Ni, W., Shu, J., Song, M.: Location and emergency inventory pre-positioning for disaster response operations: min-max robust model and a case study of Yushu earthquake. Prod. Oper. Manag. 27(1), 160–183 (2018)
Rawls, C.G., Turnquist, M.A.: Pre-positioning of emergency supplies for disaster response. Transp. Res. Part B Methodol. 44(4), 521–534 (2010)
Rezaei-Malek, M., Tavakkoli-Moghaddam, R., Zahiri, B., Bozorgi-Amiri, A.: An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Comput. Ind. Eng. 94, 201–215 (2016)
Rivera-Royero, D., Galindo, G., Yie-Pinedo, R.: A dynamic model for disaster response considering prioritized demand points. Socio Econ. Plan. Sci. 55, 59–75 (2016)
Yaghmaei, N.: Disasters 2018: year in review. Technical report, Centre for Research on the Epidemiology of Disasters (CRED) (2019)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant No. 71801135), the Natural Science Foundation of Jiangsu Province (Grant No. BK20180792), the University Natural Science Research Foundation of Jiangsu Province (Grant No. 18KJB580011), and the Startup Foundation for Introducing Talent of NUIST (Grant No. 2017r061).
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Wang, Y., Gong, Z., Lev, B. (2021). A Two-Stage Stochastic Programming Model for Pre-positioning of Relief Supplies. In: Xu, J., Duca, G., Ahmed, S., García Márquez, F., Hajiyev, A. (eds) Proceedings of the Fourteenth International Conference on Management Science and Engineering Management. ICMSEM 2020. Advances in Intelligent Systems and Computing, vol 1191. Springer, Cham. https://doi.org/10.1007/978-3-030-49889-4_4
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DOI: https://doi.org/10.1007/978-3-030-49889-4_4
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