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Integrating GIS in reorganizing blood supply network in a robust-stochastic approach by combating disruption damages

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  • Gilani Larimi, Niloofar
  • Azhdari, Abolghasem
  • Ghousi, Rouzbeh
  • Du, Bo

Abstract

As supplying adequate blood in multiple countries has failed due to the Covid-19 pandemic, the importance of redesigning a sensible protective-resilience blood supply chain is underscored. The outbreak-as an extensive disruption-has caused a delay in ordering and delivering blood and its by-products, which leads to severe social and financial loss to healthcare organizations. This paper presents a robust multi-phase optimization approach to model a blood supply network ensuring blood is collected efficiently. We evaluate the effectiveness of the model using real-world data from two mechanisms. Firstly, a Geographic Information System (GIS)-based method is presented to find potential alternative locations for blood donation centers to maximize availability, accessibility, and proximity to blood donors. Then, a protective mathematical model is developed with the incorporation of (a) blood perishability, (b) efficient collation centers, (c) multiple-source of suppliers, (d) back-up centers, (e) capacity limitation, and (f) uncertain demand. Emergency back-up for laboratory centers to supplement and offset the processing plants against the possible disorders is applied in a two-stage stochastic robust optimization model to maximize the level of hospitals' coverage. The results highlight the fraction cost of considering back-up facilities in the total costs and provide more resilient decisions with lower risks by examining resource limitations.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:soceps:v:82:y:2022:i:pa:s0038012122000283
    DOI: 10.1016/j.seps.2022.101250
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    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. Wang, Changjun & Chen, Shutong, 2020. "A distributionally robust optimization for blood supply network considering disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    3. Li, Yuchen & Zhang, Jianghua & Yu, Guodong, 2020. "A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    4. Dell’Ovo, Marta & Capolongo, Stefano & Oppio, Alessandra, 2018. "Combining spatial analysis with MCDA for the siting of healthcare facilities," Land Use Policy, Elsevier, vol. 76(C), pages 634-644.
    5. Govindan, Kannan & Mina, Hassan & Alavi, Behrouz, 2020. "A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    6. Mohammad Reza Ghatreh Samani & Seyyed-Mahdi Hosseini-Motlagh & Maryam Izadidoost Sheshkol & Seyyed-Nader Shetab-Boushehri, 2019. "A bi-objective integrated model for the uncertain blood network design with raising products quality," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 13(5), pages 553-588.
    7. Özceylan, Eren & Çetinkaya, Cihan & Erbaş, Mehmet & Kabak, Mehmet, 2016. "Logistic performance evaluation of provinces in Turkey: A GIS-based multi-criteria decision analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 323-337.
    8. Andres F. Osorio & Sally C. Brailsford & Honora K. Smith, 2015. "A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7191-7212, December.
    9. Katsaliaki, Korina, 2008. "Cost-effective practices in the blood service sector," Health Policy, Elsevier, vol. 86(2-3), pages 276-287, May.
    10. Fan, Di & Lo, Chris K.Y. & Zhou, Yi, 2021. "Sustainability risk in supply bases: The role of complexity and coupling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    11. Paul, Jomon A. & Wang, Xinfang (Jocelyn), 2019. "Robust location-allocation network design for earthquake preparedness," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 139-155.
    12. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    13. 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.
    14. Liu, Kanglin & Li, Qiaofeng & Zhang, Zhi-Hai, 2019. "Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 79-101.
    15. Acar, Müge & Kaya, Onur, 2019. "A healthcare network design model with mobile hospitals for disaster preparedness: A case study for Istanbul earthquake," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 273-292.
    16. Patra, T. Devi Prasad & Jha, J.K., 2021. "A two-period newsvendor model for prepositioning with a post-disaster replenishment using Bayesian demand update," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    17. 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.
    18. 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.
    19. 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.
    20. Verikios, George, 2020. "The dynamic effects of infectious disease outbreaks: the case of pandemic influenza and human coronavirus," MPRA Paper 104434, University Library of Munich, Germany.
    21. 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).
    22. 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.
    23. Francesca Maggioni & Stein Wallace, 2012. "Analyzing the quality of the expected value solution in stochastic programming," Annals of Operations Research, Springer, vol. 200(1), pages 37-54, November.
    24. Comber, Alexis & Dickie, Jennifer & Jarvis, Claire & Phillips, Martin & Tansey, Kevin, 2015. "Locating bioenergy facilities using a modified GIS-based location–allocation-algorithm: Considering the spatial distribution of resource supply," Applied Energy, Elsevier, vol. 154(C), pages 309-316.
    25. 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).
    26. Samuel Ratick & Brian Meacham & Yuko Aoyama, 2008. "Locating Backup Facilities to Enhance Supply Chain Disaster Resilience," Growth and Change, Wiley Blackwell, vol. 39(4), pages 642-666, December.
    27. 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).
    28. M. Barry Dumas & Manus Rabinowitz, 1977. "Policies for Reducing Blood Wastage in Hospital Blood Banks," Management Science, INFORMS, vol. 23(10), pages 1124-1132, June.
    29. 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).
    30. Lowalekar, Harshal & Ravi, R. Raghavendra, 2017. "Revolutionizing blood bank inventory management using the TOC thinking process: An Indian case study," International Journal of Production Economics, Elsevier, vol. 186(C), pages 89-122.
    31. Hanks, Robert W. & Lunday, Brian J. & Weir, Jeffery D., 2020. "Robust goal programming for multi-objective optimization of data-driven problems: A use case for the United States transportation command's liner rate setting problem," Omega, Elsevier, vol. 90(C).
    32. Murray, Alan T., 2021. "Contemporary optimization application through geographic information systems," Omega, Elsevier, vol. 99(C).
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    2. Kamran, Mehdi A. & Kia, Reza & Goodarzian, Fariba & Ghasemi, Peiman, 2023. "A new vaccine supply chain network under COVID-19 conditions considering system dynamic: Artificial intelligence algorithms," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).

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