An enhanced procedure for managing blood supply chain under disruptions and uncertainties

Mohammad Reza Ghatreh Samani () and Seyyed-Mahdi Hosseini-Motlagh ()
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Mohammad Reza Ghatreh Samani: Iran University of Science and Technology
Seyyed-Mahdi Hosseini-Motlagh: Iran University of Science and Technology

Annals of Operations Research, 2019, vol. 283, issue 1, No 55, 1413-1462

Abstract: Abstract As a service-oriented supply chain, blood supply chain management deals with a human-to-human network involved with a number of direct challenges such as irregularity in both blood supply and demand as well as multiplicity of blood products, their respective lifetimes and perishability. Besides, facing risks originating from natural disasters or man-made incidents such as labor strikes, economic problems, and so on, and from uncertainty embedded in the input data is also a real highlight in designing and managing a blood supply chain network. This paper addresses an enhanced perspective incorporating a two-phase preemptive policy by which the disruption risk is diminished through a hybrid technique using the fuzzy analytic hierarchy process and grey rational analysis for determining supplementary blood facilities, to cooperate in production process and decrease interruptions. Furthermore, a p-robust formulation is presented to control the network reliability under disruption scenarios at minimum cost. To protect the network against the uncertainty, a consolidated approach based on a recently developed fuzzy measure is extended. We also examine the validity and practicality of the proposed model and its solution perspective along with the reliability of the network by a real case of Iran. It is worth nothing that the problems in the case of disasters in which the impact of the two risk streams will be felt most keenly, could benefit from the proposed procedure advantages since it develops a proactive and controlling approach which can be extensively applicable in disastrous situation.

Keywords: Blood supply chain; Fuzzy analytic hierarchy process; Grey rational analysis; Disruption risk; Fuzzy-robust programming; P-robustness (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (15)

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DOI: 10.1007/s10479-018-2873-4

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