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Tutorial on constructing a red blood cell inventory management system with two demand rates

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  • Kopach, Renata
  • Balcioglu, Baris
  • Carter, Michael

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  • Kopach, Renata & Balcioglu, Baris & Carter, Michael, 2008. "Tutorial on constructing a red blood cell inventory management system with two demand rates," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1051-1059, March.
    • Handle: RePEc:eee:ejores:v:185:y:2008:i:3:p:1051-1059
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    1. Morris A. Cohen, 1976. "Analysis of Single Critical Number Ordering Policies for Perishable Inventories," Operations Research, INFORMS, vol. 24(4), pages 726-741, August.
    2. D. Perry & M. J. M. Posner, 1990. "Control of input and demand rates in inventory systems of perishable commodities," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(1), pages 85-97, February.
    3. Tekin, Eylem & Gurler, Ulku & Berk, Emre, 2001. "Age-based vs. stock level control policies for a perishable inventory system," European Journal of Operational Research, Elsevier, vol. 134(2), pages 309-329, October.
    4. Stephen C. Graves, 1982. "The Application of Queueing Theory to Continuous Perishable Inventory Systems," Management Science, INFORMS, vol. 28(4), pages 400-406, April.
    5. Brant E. Fries, 1975. "Optimal Ordering Policy for a Perishable Commodity with Fixed Lifetime," Operations Research, INFORMS, vol. 23(1), pages 46-61, February.
    6. Gregory P. Prastacos, 1984. "Blood Inventory Management: An Overview of Theory and Practice," Management Science, INFORMS, vol. 30(7), pages 777-800, July.
    7. Dan Chazan & Shmuel Gal, 1977. "A Markovian Model for a Perishable Product Inventory," Management Science, INFORMS, vol. 23(5), pages 512-521, January.
    8. Steven Nahmias, 1976. "Myopic Approximations for the Perishable Inventory Problem," Management Science, INFORMS, vol. 22(9), pages 1002-1008, May.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Twumasi, Clement & Twumasi, Juliet, 2022. "Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1258-1277.
    6. Vahid Sarhangian & Hossein Abouee-Mehrizi & Opher Baron & Oded Berman, 2018. "Threshold-Based Allocation Policies for Inventory Management of Red Blood Cells," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 347-362, May.
    7. Dehghani, Maryam & Abbasi, Babak & Oliveira, Fabricio, 2021. "Proactive transshipment in the blood supply chain: A stochastic programming approach," Omega, Elsevier, vol. 98(C).
    8. 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.
    9. Mahmut Parlar & David Perry & Wolfgang Stadje, 2011. "FIFO Versus LIFO Issuing Policies for Stochastic Perishable Inventory Systems," Methodology and Computing in Applied Probability, Springer, vol. 13(2), pages 405-417, June.
    10. Dillon, Mary & Oliveira, Fabricio & Abbasi, Babak, 2017. "A two-stage stochastic programming model for inventory management in the blood supply chain," International Journal of Production Economics, Elsevier, vol. 187(C), pages 27-41.
    11. Manish Shukla & Sanjay Jharkharia, 2014. "An inventory model for continuously deteriorating agri-fresh produce: an artificial immune system-based solution approach," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 9(1/2), pages 110-135.
    12. Civelek, Ismail & Karaesmen, Itir & Scheller-Wolf, Alan, 2015. "Blood platelet inventory management with protection levels," European Journal of Operational Research, Elsevier, vol. 243(3), pages 826-838.
    13. Broyles, James R. & Cochran, Jeffery K. & Montgomery, Douglas C., 2010. "A statistical Markov chain approximation of transient hospital inpatient inventory," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1645-1657, December.
    14. 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.
    15. 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.
    16. Wang, Ke-Ming & Ma, Zu-Jun, 2015. "Age-based policy for blood transshipment during blood shortage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 166-183.
    17. Pahl, Julia & Voß, Stefan, 2014. "Integrating deterioration and lifetime constraints in production and supply chain planning: A survey," European Journal of Operational Research, Elsevier, vol. 238(3), pages 654-674.
    18. Glasgow, Simon M. & Perkins, Zane B. & Tai, Nigel R.M. & Brohi, Karim & Vasilakis, Christos, 2018. "Development of a discrete event simulation model for evaluating strategies of red blood cell provision following mass casualty events," European Journal of Operational Research, Elsevier, vol. 270(1), pages 362-374.

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