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Rotating the medical supplies for emergency response: A simulation based approach

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  • Zhou, Quan Spring
  • Olsen, Tava Lennon

Abstract

Serious expiration problems exist in national medical reserves prepared for emergency response. One alternative to reduce expiration is to rotate the reserve to hospitals so products can be used for day to day operations. Yet, rotation incurs extra handling costs and needs to be combined with hospitals' ordering decisions. This decision process is complex and involves various sources of uncertainty. In this paper, we use discrete-event simulation to model the rotation of the reserve in combination with the hospitals’ inventory management, and combine it with optimization to search for the optimal rotation policy. With simulation experiments, we evaluate the performance of rotation policies and analyze the impact of emergencies, multiple hospitals with fixed costs, perishability in hospitals, and lead time. Simulation results highlight the different impact of these factors on the rotation performance, and make suggestions to address these concerns. It is also observed that, while rotation could generate significant cost savings, it is not always optimal to totally eliminate expiration.

Suggested Citation

  • Zhou, Quan Spring & Olsen, Tava Lennon, 2018. "Rotating the medical supplies for emergency response: A simulation based approach," International Journal of Production Economics, Elsevier, vol. 196(C), pages 1-11.
  • Handle: RePEc:eee:proeco:v:196:y:2018:i:c:p:1-11
    DOI: 10.1016/j.ijpe.2017.11.010
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    Cited by:

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    2. Ying Yang & Huijing Wu & Caixia Yan, 2021. "Medical consumable usage control based on Canopy_K-means clustering and WARM," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 722-739, November.
    3. Rivera-Royero, Daniel & Galindo, Gina & Yie-Pinedo, Ruben, 2020. "Planning the delivery of relief supplies upon the occurrence of a natural disaster while considering the assembly process of the relief kits," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
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    5. Ying Yang & Huijing Wu & Caixia Yan, 0. "Medical consumable usage control based on Canopy_K-means clustering and WARM," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-18.

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