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Supplier selection and pre-positioning strategy in humanitarian relief

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  • Hu, Shaolong
  • Dong, Zhijie Sasha

Abstract

Pre-positioning of relief supplies is one important preparedness action for natural disasters. This paper proposes the importance of supplier selection in humanitarian relief, and integrates it into the pre-positioning strategy. These suppliers have own physical inventories for regular business, and relief agencies are assumed to be able to use such inventories for disaster response by providing compensation. The supplier selection criteria include price discounts offered by suppliers based on order quantity and required lead time as well as physical inventory. By considering disruption risks, this paper presents a two-stage stochastic programming model to produce plans including facility location and inventory, supplier selection, and distribution of relief supplies. A case study focused on hurricane threats in the Gulf Coast area of the US illustrates the application of the proposed model. Sensitivity analysis of comparison experiments offers managerial insights for relief agencies.

Suggested Citation

  • Hu, Shaolong & Dong, Zhijie Sasha, 2019. "Supplier selection and pre-positioning strategy in humanitarian relief," Omega, Elsevier, vol. 83(C), pages 287-298.
  • Handle: RePEc:eee:jomega:v:83:y:2019:i:c:p:287-298
    DOI: 10.1016/j.omega.2018.10.011
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    1. Dufour, Émilie & Laporte, Gilbert & Paquette, Julie & Rancourt, Marie–Ève, 2018. "Logistics service network design for humanitarian response in East Africa," Omega, Elsevier, vol. 74(C), pages 1-14.
    2. Baskaya, Serhat & Ertem, Mustafa Alp & Duran, Serhan, 2017. "Pre-positioning of relief items in humanitarian logistics considering lateral transhipment opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 50-60.
    3. Jingxian Chen & Liang Liang & Dong-Qing Yao, 2017. "Pre-positioning of relief inventories for non-profit organizations: a newsvendor approach," Annals of Operations Research, Springer, vol. 259(1), pages 35-63, December.
    4. Rawls, Carmen G. & Turnquist, Mark A., 2010. "Pre-positioning of emergency supplies for disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 521-534, May.
    5. Wenjun Ni & Jia Shu & Miao Song, 2018. "Location and Emergency Inventory Pre†Positioning for Disaster Response Operations: Min†Max Robust Model and a Case Study of Yushu Earthquake," Production and Operations Management, Production and Operations Management Society, vol. 27(1), pages 160-183, January.
    6. J.H. Ruan & X.P. Wang & F.T.S. Chan & Y. Shi, 2016. "Optimizing the intermodal transportation of emergency medical supplies using balanced fuzzy clustering," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4368-4386, July.
    7. Li, Lei & Zabinsky, Zelda B., 2011. "Incorporating uncertainty into a supplier selection problem," International Journal of Production Economics, Elsevier, vol. 134(2), pages 344-356, December.
    8. Cantillo, Victor & Serrano, Iván & Macea, Luis F. & Holguín-Veras, José, 2018. "Discrete choice approach for assessing deprivation cost in humanitarian relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 33-46.
    9. Qian, Li, 2014. "Market-based supplier selection with price, delivery time, and service level dependent demand," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 697-706.
    10. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    11. Mansini, Renata & Savelsbergh, Martin W.P. & Tocchella, Barbara, 2012. "The supplier selection problem with quantity discounts and truckload shipping," Omega, Elsevier, vol. 40(4), pages 445-455.
    12. Burcu Balcik & Deniz Ak, 2014. "Supplier Selection for Framework Agreements in Humanitarian Relief," Production and Operations Management, Production and Operations Management Society, vol. 23(6), pages 1028-1041, June.
    13. Hammami, Ramzi & Temponi, Cecilia & Frein, Yannick, 2014. "A scenario-based stochastic model for supplier selection in global context with multiple buyers, currency fluctuation uncertainties, and price discounts," European Journal of Operational Research, Elsevier, vol. 233(1), pages 159-170.
    14. Hosseini, Seyedmohsen & Barker, Kash, 2016. "A Bayesian network model for resilience-based supplier selection," International Journal of Production Economics, Elsevier, vol. 180(C), pages 68-87.
    15. Lawrence V. Snyder & Zümbül Atan & Peng Peng & Ying Rong & Amanda J. Schmitt & Burcu Sinsoysal, 2016. "OR/MS models for supply chain disruptions: a review," IISE Transactions, Taylor & Francis Journals, vol. 48(2), pages 89-109, February.
    16. PrasannaVenkatesan, S. & Goh, M., 2016. "Multi-objective supplier selection and order allocation under disruption risk," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 124-142.
    17. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
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