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Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

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  • Afshin Kamyabniya

    (Yazd University
    Purdue University)

  • M. M. Lotfi

    (Yazd University)

  • Mohsen Naderpour

    (University of Technology Sydney (UTS))

  • Yuehwern Yih

    (Purdue University)

Abstract

Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation.

Suggested Citation

  • Afshin Kamyabniya & M. M. Lotfi & Mohsen Naderpour & Yuehwern Yih, 2018. "Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach," Information Systems Frontiers, Springer, vol. 20(4), pages 759-782, August.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:4:d:10.1007_s10796-017-9788-5
    DOI: 10.1007/s10796-017-9788-5
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    Cited by:

    1. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2020. "Toward a coordination of inventory and distribution schedules for blood in disasters," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    2. Christian Kauten & Ashish Gupta & Xiao Qin & Glenn Richey, 2022. "Predicting Blood Donors Using Machine Learning Techniques," Information Systems Frontiers, Springer, vol. 24(5), pages 1547-1562, October.
    3. Sara Cheraghi & Seyyed-Mahdi Hosseini-Motlagh, 2020. "Responsive and reliable injured-oriented blood supply chain for disaster relief: a real case study," Annals of Operations Research, Springer, vol. 291(1), pages 129-167, August.
    4. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    5. Asadpour, Milad & Olsen, Tava Lennon & Boyer, Omid, 2022. "An updated review on blood supply chain quantitative models: A disaster perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    6. Ghassan Beydoun & Sergiu Dascalu & Dale Dominey-Howes & Andrew Sheehan, 2018. "Disaster Management and Information Systems: Insights to Emerging Challenges," Information Systems Frontiers, Springer, vol. 20(4), pages 649-652, August.
    7. 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).
    8. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Cheraghi, Sara, 2020. "Robust and stable flexible blood supply chain network design under motivational initiatives," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

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