IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v319y2022i1d10.1007_s10479-021-03978-5.html
   My bibliography  Save this article

Blood supply planning during natural disasters under uncertainty: a novel bi-objective model and an application for red crescent

Author

Listed:
  • Elmira Farrokhizadeh

    (Istanbul Technical University)

  • Seyed Amin Seyfi-Shishavan

    (Istanbul Technical University)

  • Sule Itir Satoglu

    (Istanbul Technical University)

Abstract

In natural disasters, having a capable network of collecting and distributing crucial items such as blood is one of the major concerns. However, due to damage to the infrastructure after disasters, mobile blood collecting facilities (blood mobiles) are usually required. This paper aims to decide the locations of mobile facilities in each period for collecting donated blood, plan the blood distribution from the fixed and mobile facilities to the main blood centers, as well as from blood centers to the hospitals and field-hospitals, under uncertain conditions. To do so, a multi-period, bi-objective mixed-integer mathematical model is developed under a multiple-scenario, aiming to minimize the unsatisfied blood demand as well as the total cost of the network. In the proposed model, the blood group compatibility matrix, failure rate of the facilities, and patients’ urgency levels are considered. An augmented ε-constraint method is applied to solve this bi-objective model. Due to the complex nature of the proposed blood supply chain model, the Lagrangian relaxation approach is used to solve the proposed model. An expected Istanbul earthquake is considered, and the blood supply planning through the Red Crescent’s European branch is performed utilizing the proposed model to examine its validity. According to the numerical results, the mobile facilities' locations in each period under each scenario are determined, the unsatisfied demand in each hospital and field-hospital for each blood type are reported, and the tradeoff between the supply chain costs and unsatisfied demand are discussed in detail. Finally, to illustrate the robustness of the proposed model, a detailed sensitivity analysis is performed. According to the study results, opening new blood centers near the high-demand sub-districts for faster testing and supply, increasing the hospitals' capacities, and usage of drones and helicopters for blood distribution are suggested can be considered as managerial insights.

Suggested Citation

  • Elmira Farrokhizadeh & Seyed Amin Seyfi-Shishavan & Sule Itir Satoglu, 2022. "Blood supply planning during natural disasters under uncertainty: a novel bi-objective model and an application for red crescent," Annals of Operations Research, Springer, vol. 319(1), pages 73-113, December.
  • Handle: RePEc:spr:annopr:v:319:y:2022:i:1:d:10.1007_s10479-021-03978-5
    DOI: 10.1007/s10479-021-03978-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-021-03978-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-021-03978-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kamali, Behrooz & Bish, Douglas & Glick, Roger, 2017. "Optimal service order for mass-casualty incident response," European Journal of Operational Research, Elsevier, vol. 261(1), pages 355-367.
    2. Mohamadreza Fazli-Khalaf & Soheyl Khalilpourazari & Mohammad Mohammadi, 2019. "Mixed robust possibilistic flexible chance constraint optimization model for emergency blood supply chain network design," Annals of Operations Research, Springer, vol. 283(1), pages 1079-1109, December.
    3. 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.
    4. Andres F. Osorio & Sally C. Brailsford & Honora K. Smith & Sonia P. Forero-Matiz & Bernardo A. Camacho-Rodríguez, 2017. "Simulation-optimization model for production planning in the blood supply chain," Health Care Management Science, Springer, vol. 20(4), pages 548-564, December.
    5. Alex F. Mills & Nilay Tanık Argon & Serhan Ziya, 2013. "Resource-Based Patient Prioritization in Mass-Casualty Incidents," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 361-377, July.
    6. Soheyl Khalilpourazari & Alireza Arshadi Khamseh, 2019. "Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application," Annals of Operations Research, Springer, vol. 283(1), pages 355-393, December.
    7. Behzad Zahiri & Mir Saman Pishvaee, 2017. "Blood supply chain network design considering blood group compatibility under uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2013-2033, April.
    8. Repoussis, Panagiotis P. & Paraskevopoulos, Dimitris C. & Vazacopoulos, Alkiviadis & Hupert, Nathaniel, 2016. "Optimizing emergency preparedness and resource utilization in mass-casualty incidents," European Journal of Operational Research, Elsevier, vol. 255(2), pages 531-544.
    9. Mohammad Reza Ghatreh Samani & Seyyed-Mahdi Hosseini-Motlagh, 2019. "An enhanced procedure for managing blood supply chain under disruptions and uncertainties," Annals of Operations Research, Springer, vol. 283(1), pages 1413-1462, December.
    10. Duan, Qinglin & Liao, T. Warren, 2014. "Optimization of blood supply chain with shortened shelf lives and ABO compatibility," International Journal of Production Economics, Elsevier, vol. 153(C), pages 113-129.
    11. Rameshwar Dubey & Nezih Altay & Constantin Blome, 2019. "Swift trust and commitment: The missing links for humanitarian supply chain coordination?," Annals of Operations Research, Springer, vol. 283(1), pages 159-177, December.
    12. Imai, Akio & Nishimura, Etsuko & Current, John, 2007. "A Lagrangian relaxation-based heuristic for the vehicle routing with full container load," European Journal of Operational Research, Elsevier, vol. 176(1), pages 87-105, January.
    13. Angappa Gunasekaran & Rameshwar Dubey & Samuel Fosso Wamba & Thanos Papadopoulos & Benjamin T. Hazen & Eric W.T. Ngai, 2018. "Bridging humanitarian operations management and organisational theory," International Journal of Production Research, Taylor & Francis Journals, vol. 56(21), pages 6735-6740, November.
    14. Bérubé, Jean-François & Gendreau, Michel & Potvin, Jean-Yves, 2009. "An exact [epsilon]-constraint method for bi-objective combinatorial optimization problems: Application to the Traveling Salesman Problem with Profits," European Journal of Operational Research, Elsevier, vol. 194(1), pages 39-50, April.
    15. Fahimnia, Behnam & Jabbarzadeh, Armin & Ghavamifar, Ali & Bell, Michael, 2017. "Supply chain design for efficient and effective blood supply in disasters," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 700-709.
    16. Rameshwar Dubey & Angappa Gunasekaran & David J. Bryde & Yogesh K. Dwivedi & Thanos Papadopoulos, 2020. "Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3381-3398, June.
    17. 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.
    18. Anna Nagurney & Amir Masoumi & Min Yu, 2012. "Supply chain network operations management of a blood banking system with cost and risk minimization," Computational Management Science, Springer, vol. 9(2), pages 205-231, May.
    19. M. Ülkü & Kathryn Bell & Stephanie Wilson, 2015. "Modeling the impact of donor behavior on humanitarian aid operations," Annals of Operations Research, Springer, vol. 230(1), pages 153-168, July.
    20. Rameshwar Dubey & Angappa Gunasekaran & Thanos Papadopoulos, 2019. "Disaster relief operations: past, present and future," Annals of Operations Research, Springer, vol. 283(1), pages 1-8, December.
    21. Ramezanian, Reza & Behboodi, Zahra, 2017. "Blood supply chain network design under uncertainties in supply and demand considering social aspects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 69-82.
    22. 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).
    23. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Roubaud, David & Fosso Wamba, Samuel & Giannakis, Mihalis & Foropon, Cyril, 2019. "Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 210(C), pages 120-136.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. Tirkolaee, Erfan Babaee & Golpîra, Hêriş & Javanmardan, Ahvan & Maihami, Reza, 2023. "A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    4. Javid Ghahremani-Nahr & Ramez Kian & Ehsan Sabet & Vahid Akbari, 2022. "A bi-objective blood supply chain model under uncertain donation, demand, capacity and cost: a robust possibilistic-necessity approach," Operational Research, Springer, vol. 22(5), pages 4685-4723, November.
    5. 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).
    6. Amir Jamali & Amirhossein Ranjbar & Jafar Heydari & Sina Nayeri, 2022. "A multi-objective stochastic programming model to configure a sustainable humanitarian logistics considering deprivation cost and patient severity," Annals of Operations Research, Springer, vol. 319(1), pages 1265-1300, December.
    7. Mohammad Reza Ghatreh Samani & Seyyed-Mahdi Hosseini-Motlagh, 2019. "An enhanced procedure for managing blood supply chain under disruptions and uncertainties," Annals of Operations Research, Springer, vol. 283(1), pages 1413-1462, December.
    8. M. Rezaei Kallaj & M. Hasannia Kolaee & S. M. J. Mirzapour Al-e-hashem, 2023. "Integrating bloodmobiles and drones in a post-disaster blood collection problem considering blood groups," Annals of Operations Research, Springer, vol. 321(1), pages 783-811, February.
    9. 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).
    10. Josip Marić & Carlos Galera-Zarco & Marco Opazo-Basáez, 2022. "The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1003-1044, December.
    11. 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).
    12. Rameshwar Dubey & David J. Bryde & Cyril Foropon & Gary Graham & Mihalis Giannakis & Deepa Bhatt Mishra, 2022. "Agility in humanitarian supply chain: an organizational information processing perspective and relational view," Annals of Operations Research, Springer, vol. 319(1), pages 559-579, December.
    13. Diabat, Ali & Jabbarzadeh, Armin & Khosrojerdi, Amir, 2019. "A perishable product supply chain network design problem with reliability and disruption considerations," International Journal of Production Economics, Elsevier, vol. 212(C), pages 125-138.
    14. Mohammad Reza Ghatreh Samani & Seyyed-Mahdi Hosseini-Motlagh, 2021. "A robust framework for designing blood network in disaster relief: a real-life case," Operational Research, Springer, vol. 21(3), pages 1529-1568, September.
    15. 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.
    16. Meneses, Maria & Santos, Daniel & Barbosa-Póvoa, Ana, 2023. "Modelling the Blood Supply Chain," European Journal of Operational Research, Elsevier, vol. 307(2), pages 499-518.
    17. Sachin Modgil & Rohit Kumar Singh & Cyril Foropon, 2022. "Quality management in humanitarian operations and disaster relief management: a review and future research directions," Annals of Operations Research, Springer, vol. 319(1), pages 1045-1098, December.
    18. Nagurney, Anna & Dutta, Pritha, 2019. "Competition for blood donations," Omega, Elsevier, vol. 85(C), pages 103-114.
    19. Mahsa Pouraliakbari-Mamaghani & Ali Ghodratnama & Seyed Hamid Reza Pasandideh & Ahmed Saif, 2022. "A robust possibilistic programming approach for blood supply chain network design in disaster relief considering congestion," Operational Research, Springer, vol. 22(3), pages 1987-2032, July.
    20. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:319:y:2022:i:1:d:10.1007_s10479-021-03978-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.