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An age-based lateral-transshipment policy for perishable items

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  • Dehghani, Maryam
  • Abbasi, Babak

Abstract

Lateral transshipment is an efficient policy designed to improve the performance of a supply chain. Despite the importance of transshipment for perishable items, few studies consider the issue of perishability. Currently, transshipment in some blood supply chains is based on the age profile of units in hospitals. However, decisions such as the age threshold are made empirically and are fixed for all hospitals. In this paper, we propose a new transshipment policy for perishable items based on the age of the oldest item in the system to improve supply-chain performance. The proposed model has applications for transshipping blood units between hospitals. We develop a heuristic solution using partial differential equations to compute performance measures and cost function. The results demonstrate that our transshipment policy is effective under various circumstances such as lost sale and backordering. We also compare the performance of the suggested transshipment policy to the transshipment policy that is currently practiced in some Australian hospitals (which is an aged based proactive transshipment policy with an empirically set threshold). The results demonstrate that by setting the optimal threshold, hospitals could transfuse units with the same average age of the current policy, while reducing their total inventory cost by approximately 61%.

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  • 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.
  • Handle: RePEc:eee:proeco:v:198:y:2018:i:c:p:93-103
    DOI: 10.1016/j.ijpe.2018.01.028
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    4. Dehghani, Maryam & Abbasi, Babak & Oliveira, Fabricio, 2021. "Proactive transshipment in the blood supply chain: A stochastic programming approach," Omega, Elsevier, vol. 98(C).
    5. Naderi, Siamak & Kilic, Kemal & Dasci, Abdullah, 2020. "A deterministic model for the transshipment problem of a fast fashion retailer under capacity constraints," International Journal of Production Economics, Elsevier, vol. 227(C).
    6. Lee, Junhyeok & Shin, Youngchul & Moon, Ilkyeong, 2024. "A hybrid deep reinforcement learning approach for a proactive transshipment of fresh food in the online–offline channel system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    7. Mohsen Momenitabar & Zhila Dehdari Ebrahimi & Mohammad Arani & Jeremy Mattson, 2023. "Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply," Annals of Operations Research, Springer, vol. 328(1), pages 859-901, September.
    8. 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).
    9. Sohrabi, Mahnaz & Zandieh, Mostafa & Shokouhifar, Mohammad, 2023. "Sustainable inventory management in blood banks considering health equity using a combined metaheuristic-based robust fuzzy stochastic programming," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    10. Gilani Larimi, Niloofar & Yaghoubi, Saeed & Hosseini-Motlagh, Seyyed-Mahdi, 2019. "Itemized platelet supply chain with lateral transshipment under uncertainty evaluating inappropriate output in laboratories," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    11. Esmaeili, Somayeh & Bashiri, Mahdi & Amiri, Amirhossein, 2023. "An exact criterion space search algorithm for a bi-objective blood collection problem," European Journal of Operational Research, Elsevier, vol. 311(1), pages 210-232.

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