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Better management of blood supply-chain with GIS-based analytics

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  • Dursun Delen
  • Madhav Erraguntla
  • Richard Mayer
  • Chang-Nien Wu

Abstract

This paper presents a novel application of operations research, data mining and geographic information-systems-based analytics to support decision making in blood supply chain management. This, blood reserve availability assessment, tracking, and management system (BRAMS), research project has been funded by the Office of the Secretary of Defense. (This DoD funded SBIR project is performed by the researchers at Knowledge Based Systems, Inc. (KBSI).) The rapidly increasing demand, criticality of the product, strict storage and handling requirements, and the vastness of the theater of operations, make blood supply-chain management a complex, yet vital problem for the department of defense. In order to address this problem a variety of contemporary analytic techniques are used to analyze inventory and consumption patterns, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The current implementation of the system is being actively used by 130 mangers at different levels in the supply chain including facilities at Osan Air Force Base in South Korea and Incirlik Air Force Base in Turkey. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Dursun Delen & Madhav Erraguntla & Richard Mayer & Chang-Nien Wu, 2011. "Better management of blood supply-chain with GIS-based analytics," Annals of Operations Research, Springer, vol. 185(1), pages 181-193, May.
    • Handle: RePEc:spr:annopr:v:185:y:2011:i:1:p:181-193:10.1007/s10479-009-0616-2
    DOI: 10.1007/s10479-009-0616-2
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    Cited by:

    1. Jabbarzadeh, Armin & Fahimnia, Behnam & Seuring, Stefan, 2014. "Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 225-244.
    2. Anna Nagurney & Pritha Dutta, 2019. "Supply chain network competition among blood service organizations: a Generalized Nash Equilibrium framework," Annals of Operations Research, Springer, vol. 275(2), pages 551-586, April.
    3. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    4. Faraz Salehi & Masoud Mahootchi & Seyed Mohammad Moattar Husseini, 2019. "Developing a robust stochastic model for designing a blood supply chain network in a crisis: a possible earthquake in Tehran," Annals of Operations Research, Springer, vol. 283(1), pages 679-703, December.
    5. De Boeck, Kim & Decouttere, Catherine & Jónasson, Jónas Oddur & Vandaele, Nico, 2022. "Vaccine supply chains in resource-limited settings: Mitigating the impact of rainy season disruptions," European Journal of Operational Research, Elsevier, vol. 301(1), pages 300-317.
    6. Turgay Ayer & Can Zhang & Chenxi Zeng & Chelsea C. White III & V. Roshan Joseph, 2019. "Analysis and Improvement of Blood Collection Operations," Service Science, INFORMS, vol. 21(1), pages 29-46, January.
    7. Liu, Wenqian & Ke, Ginger Y. & Chen, Jian & Zhang, Lianmin, 2020. "Scheduling the distribution of blood products: A vendor-managed inventory routing approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    8. Sameer Prasad & Rimi Zakaria & Nezih Altay, 2018. "Big data in humanitarian supply chain networks: a resource dependence perspective," Annals of Operations Research, Springer, vol. 270(1), pages 383-413, November.
    9. Gunpinar, Serkan & Centeno, Grisselle, 2016. "An integer programming approach to the bloodmobile routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 94-115.
    10. Gilani Larimi, Niloofar & Azhdari, Abolghasem & Ghousi, Rouzbeh & Du, Bo, 2022. "Integrating GIS in reorganizing blood supply network in a robust-stochastic approach by combating disruption damages," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    11. Donya Rahmani, 2019. "Designing a robust and dynamic network for the emergency blood supply chain with the risk of disruptions," Annals of Operations Research, Springer, vol. 283(1), pages 613-641, December.
    12. Hamdan, Bayan & Diabat, Ali, 2020. "Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    13. Bhuvnesh Sharma & M. Ramkumar & Nachiappan Subramanian & Bharat Malhotra, 2019. "Dynamic temporary blood facility location-allocation during and post-disaster periods," Annals of Operations Research, Springer, vol. 283(1), pages 705-736, December.
    14. Beliën, Jeroen & Forcé, Hein, 2012. "Supply chain management of blood products: A literature review," European Journal of Operational Research, Elsevier, vol. 217(1), pages 1-16.
    15. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    16. Bruno, Giuseppe & Diglio, Antonio & Piccolo, Carmela & Cannavacciuolo, Lorella, 2019. "Territorial reorganization of regional blood management systems: Evidences from an Italian case study," Omega, Elsevier, vol. 89(C), pages 54-70.

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