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Blood plasma supply chain planning to respond COVID-19 pandemic: a case study
Ali Fallahi1, Seyed Alireza Mousavian Anaraki2, Hadi Mokhtari3
1Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran.
Insights
This study introduces the first integrated green supply chain for COVID-19 convalescent plasma, optimizing cost and carbon emissions. It highlights the significant impact of regular plasma flow and demand on network efficiency.
Area of Science:
- Operations Research
- Supply Chain Management
- Public Health
Background:
- COVID-19 necessitates efficient management of convalescent plasma for patient care.
- Existing research lacks a dedicated supply chain framework for convalescent plasma during pandemics.
- Environmental concerns require a focus on reducing carbon emissions in healthcare logistics.
Purpose of the Study:
- To develop the first integrated green supply chain network for both regular and convalescent plasma during the COVID-19 pandemic.
- To optimize network design by minimizing total cost and total carbon emissions simultaneously.
- To address the unique challenges of managing convalescent plasma within a pandemic context.
Main Methods:
- Formulation of a mixed-integer multi-objective optimization model.
- Application of the Epsilon constraint method to handle dual objectives.
- Case study analysis in Iran with sensitivity assessments.
Main Results:
- Product demand significantly influences both cost and carbon emission objectives.
- Total system carbon emission is highly sensitive to the flow of regular plasma.
- Transportation emission unit changes impact total emission but not total cost.
Conclusions:
- The proposed model provides a novel framework for pandemic-era plasma supply chains.
- Integrating environmental considerations into plasma logistics is crucial for sustainability.
- Strategic planning of plasma flow, especially regular plasma, is key to reducing carbon footprint.
Abstract:
The COVID-19 pandemic causes a severe threat to human lives worldwide. Convalescent plasma as supportive care for COVID-19 is critical in reducing the death rate and staying in hospitals. Designing an efficient supply chain network capable of managing convalescent plasma in this situation seems necessary. Although many researchers investigated supply chains of blood products, no research was conducted on the planning of convalescent plasma in the supply chain framework with specific features of COVID-19. This gap is covered in the current work by simultaneous regular and convalescent plasma flow in a supply chain network. Besides, due to the growing importance of environmental problems, the resulting carbon emission from transportation activities is viewed to provide a green network. In other words, this study aims to plan the integrated green supply chain network of regular and convalescent plasma in the pandemic outbreak of COVID-19 for the first time. The presented mixed-integer multi-objective optimization model determines optimal network decisions while minimizing the total cost and total carbon emission. The Epsilon constraint method is used to handle the considered objectives. The model is applied to a real case study from the capital of Iran. Sensitivity analyses are carried out, and managerial insights are drawn. Based on the obtained results, product demand impacts the objective functions significantly. Moreover, the systems' total carbon emission is highly dependent on the flow of regular plasma. The results also reveal that changing transportation emission unit causes significant variation in the total emission while the total cost remains fixed.
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