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An Evaluation of Blood-Inventory Policies: A Markov Chain Application

Author

Listed:
  • C. Carl Pegels

    (State University of New York, Buffalo, New York)

  • Andrew E. Jelmert

    (State University of New York, Buffalo, New York)

Abstract

A theoretical model using mainly the theory of absorbing Markov chains is applied to several human-blood-issuing policies. The objective of the model applications is to determine the effects of the issuing policies on average inventory levels, which determine blood shortage probabilities, and on the average age of blood at the time it is transfused. Issuing policies that issue (transfuse) fresher blood with a higher probability than older blood are defined as modified fifo policies, and issuing policies that issue older blood with a higher probability than fresher blood are defined as modified fifo policies. Application of the theoretical model to the various issuing policies allows complete evaluation of the policies, and a policy choice can be made on the basis of the evaluation.

Suggested Citation

  • C. Carl Pegels & Andrew E. Jelmert, 1970. "An Evaluation of Blood-Inventory Policies: A Markov Chain Application," Operations Research, INFORMS, vol. 18(6), pages 1087-1098, December.
    • Handle: RePEc:inm:oropre:v:18:y:1970:i:6:p:1087-1098
    DOI: 10.1287/opre.18.6.1087
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    Cited by:

    1. Ana Margarida Araújo & Daniel Santos & Inês Marques & Ana Barbosa-Povoa, 2020. "Blood supply chain: a two-stage approach for tactical and operational planning," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1023-1053, December.
    2. 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.
    3. 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).
    4. Dehghani, Maryam & Abbasi, Babak & Oliveira, Fabricio, 2021. "Proactive transshipment in the blood supply chain: A stochastic programming approach," Omega, Elsevier, vol. 98(C).
    5. 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.
    6. Suresha Kharvi & T. P. M. Pakkala & G. Srinivasan, 2019. "Ordering policies under currency risk sharing agreements: a Markov chain approach," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 945-964, September.
    7. 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.

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