Designing supply chain of blood under uncertainty: A case study

Ensuring an adequate and healthy blood supply is a persistent challenge that healthcare systems worldwide face. The need for blood donors and their products is constant, while the supply from donors is somewhat irregular, and the demand for these products is often unpredictable. Furthermore, the lev...

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Main Authors: Ali Namazian, Reza Babazadeh
Format: Article
Language:English
Published: Ayandegan Institute of Higher Education, 2025-03-01
Series:International Journal of Research in Industrial Engineering
Subjects:
Online Access:https://www.riejournal.com/article_202116_13738ba5497f464cd2edd3893bc536f1.pdf
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author Ali Namazian
Reza Babazadeh
author_facet Ali Namazian
Reza Babazadeh
author_sort Ali Namazian
collection DOAJ
description Ensuring an adequate and healthy blood supply is a persistent challenge that healthcare systems worldwide face. The need for blood donors and their products is constant, while the supply from donors is somewhat irregular, and the demand for these products is often unpredictable. Furthermore, the levels of demand and blood donation are uncertain. As a result, uncertainty plays a crucial role in the blood supply chain, especially during crises such as earthquakes and pandemics. In this regard, designing the  Blood Supply Chain Network (BSCN) under uncertainty is essential for meeting fluctuating demand, addressing logistical challenges, responding to emergencies, and ensuring the quality and safety of blood products throughout the supply chain. This research aims to present a Mixed-Integer Linear Programming (MIP) model under uncertainty for strategic and tactical decision-making in the blood supply chain over a determined planning horizon. The fuzzy theory approach has been used to incorporate uncertainty into the model's parameters. An interactive fuzzy solution approach based on credibility measurement has been developed to solve the fuzzy optimization model. The results obtained from designing and implementing the proposed model in a case study indicate the desirable efficiency of this model in determining the optimal number and location of facilities in a BSCN, including fixed facilities, temporary facilities, and blood banks, as well as the optimal amount of blood transfer between different entities of the blood supply chain. Furthermore, a sensitivity analysis of the parameters is performed to determine the most influential factors affecting the objective function of the problem.
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institution Kabale University
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publisher Ayandegan Institute of Higher Education,
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series International Journal of Research in Industrial Engineering
spelling doaj-art-1419168b85b04f4bb9de2bca4f0f8c782025-01-30T15:10:52ZengAyandegan Institute of Higher Education,International Journal of Research in Industrial Engineering2783-13372717-29372025-03-0114117719510.22105/riej.2024.436665.1415202116Designing supply chain of blood under uncertainty: A case studyAli Namazian0Reza Babazadeh1Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran.Department of Industrial Engineering, Faculty of Engineering, Urmia University, Urmia, Iran.Ensuring an adequate and healthy blood supply is a persistent challenge that healthcare systems worldwide face. The need for blood donors and their products is constant, while the supply from donors is somewhat irregular, and the demand for these products is often unpredictable. Furthermore, the levels of demand and blood donation are uncertain. As a result, uncertainty plays a crucial role in the blood supply chain, especially during crises such as earthquakes and pandemics. In this regard, designing the  Blood Supply Chain Network (BSCN) under uncertainty is essential for meeting fluctuating demand, addressing logistical challenges, responding to emergencies, and ensuring the quality and safety of blood products throughout the supply chain. This research aims to present a Mixed-Integer Linear Programming (MIP) model under uncertainty for strategic and tactical decision-making in the blood supply chain over a determined planning horizon. The fuzzy theory approach has been used to incorporate uncertainty into the model's parameters. An interactive fuzzy solution approach based on credibility measurement has been developed to solve the fuzzy optimization model. The results obtained from designing and implementing the proposed model in a case study indicate the desirable efficiency of this model in determining the optimal number and location of facilities in a BSCN, including fixed facilities, temporary facilities, and blood banks, as well as the optimal amount of blood transfer between different entities of the blood supply chain. Furthermore, a sensitivity analysis of the parameters is performed to determine the most influential factors affecting the objective function of the problem.https://www.riejournal.com/article_202116_13738ba5497f464cd2edd3893bc536f1.pdfblood supply chainhealthcare systemsuncertaintymixed-integer linear programming model
spellingShingle Ali Namazian
Reza Babazadeh
Designing supply chain of blood under uncertainty: A case study
International Journal of Research in Industrial Engineering
blood supply chain
healthcare systems
uncertainty
mixed-integer linear programming model
title Designing supply chain of blood under uncertainty: A case study
title_full Designing supply chain of blood under uncertainty: A case study
title_fullStr Designing supply chain of blood under uncertainty: A case study
title_full_unstemmed Designing supply chain of blood under uncertainty: A case study
title_short Designing supply chain of blood under uncertainty: A case study
title_sort designing supply chain of blood under uncertainty a case study
topic blood supply chain
healthcare systems
uncertainty
mixed-integer linear programming model
url https://www.riejournal.com/article_202116_13738ba5497f464cd2edd3893bc536f1.pdf
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AT rezababazadeh designingsupplychainofbloodunderuncertaintyacasestudy