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Age-based policy for blood transshipment during blood shortage

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  • Wang, Ke-Ming
  • Ma, Zu-Jun

Abstract

This paper introduces the properties of inventory structure for both rescue and affected banks during blood shortage. An age-based transshipment model is developed, with two preference selection methods for transshipping blood units being presented. Compared to quantity-based policy, the age-based policy under first-in-first-transship is recommended as it can reduce the expired rate more efficiently. Under simulation operating scenarios with time-varying demand and supply, we analyzed the sensitivity of parameters, which include expected supply period, shelf life and blood shortage period. Additionally, this study reveals that the transshipment decision will increase the expired ratio and the overstock ratio after blood shortage.

Suggested Citation

  • Wang, Ke-Ming & Ma, Zu-Jun, 2015. "Age-based policy for blood transshipment during blood shortage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 166-183.
    • Handle: RePEc:eee:transe:v:80:y:2015:i:c:p:166-183
    DOI: 10.1016/j.tre.2015.05.007
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    Cited by:

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    3. Dehghani, Maryam & Abbasi, Babak, 2018. "An age-based lateral-transshipment policy for perishable items," International Journal of Production Economics, Elsevier, vol. 198(C), pages 93-103.
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    5. Samani, Mohammad Reza Ghatreh & Hosseini-Motlagh, Seyyed-Mahdi & Homaei, Shamim, 2020. "A reactive phase against disruptions for designing a proactive platelet supply network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    6. Kamyabniya, Afshin & Noormohammadzadeh, Zohre & Sauré, Antoine & Patrick, Jonathan, 2021. "A robust integrated logistics model for age-based multi-group platelets in disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    7. Yuan Xu & Joseph Szmerekovsky, 2022. "A multi-product multi-period stochastic model for a blood supply chain considering blood substitution and demand uncertainty," Health Care Management Science, Springer, vol. 25(3), pages 441-459, September.
    8. Dehghani, Maryam & Abbasi, Babak & Oliveira, Fabricio, 2021. "Proactive transshipment in the blood supply chain: A stochastic programming approach," Omega, Elsevier, vol. 98(C).
    9. Gerald Oeser & Pietro Romano, 2021. "Exploring risk pooling in hospitals to reduce demand and lead time uncertainty," Operations Management Research, Springer, vol. 14(1), pages 78-94, June.
    10. Ensafian, Hamidreza & Yaghoubi, Saeed, 2017. "Robust optimization model for integrated procurement, production and distribution in platelet supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 32-55.

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