A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain. (July 2022)
- Record Type:
- Journal Article
- Title:
- A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain. (July 2022)
- Main Title:
- A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain
- Authors:
- Gilani, Hani
Sahebi, Hadi - Abstract:
- Highlights: Developing a COVID-19 vaccine supply chain based on domestic/foreign supply network. Analyzing environmental effects based on ReCiPe measures in SimaPro application. Estimating COVID-19 vaccine supply chain social effects based on ISO2600 in three indicators. Addressing robust models' high conservatism through a robust data-driven model. Using cutting hyper-planes to implement more accurate and realistic data. Validating Robust proposed model by comparing it with the box and polyhedral uncertainty set. Abstract: The worldwide COVID-19 pandemic sparked such a wave of concern that made access to vaccines more necessary than before. As the vaccine inaccessibility in developing countries has made pandemic eradication more difficult, this study has presented a mathematical model of a sustainable SC for the COVID-19 vaccine that covers the economic, environmental and social aspects and provides vaccine both domestically and internationally. It has also proposed a robust data-driven model based on a polyhedral uncertainty set to address the unjust worldwide vaccine distribution as an uncertain parameter. It is acceptably robust and is also less conservative than its classical counterparts. For validation, the model has been implemented in a real case in Iran, and the results have shown that it is 21% less conservative than its classical rivals (Box and Polyhedral convex uncertainty sets) in facing the uncertain parameter. As a result, the model proposes the constructionHighlights: Developing a COVID-19 vaccine supply chain based on domestic/foreign supply network. Analyzing environmental effects based on ReCiPe measures in SimaPro application. Estimating COVID-19 vaccine supply chain social effects based on ISO2600 in three indicators. Addressing robust models' high conservatism through a robust data-driven model. Using cutting hyper-planes to implement more accurate and realistic data. Validating Robust proposed model by comparing it with the box and polyhedral uncertainty set. Abstract: The worldwide COVID-19 pandemic sparked such a wave of concern that made access to vaccines more necessary than before. As the vaccine inaccessibility in developing countries has made pandemic eradication more difficult, this study has presented a mathematical model of a sustainable SC for the COVID-19 vaccine that covers the economic, environmental and social aspects and provides vaccine both domestically and internationally. It has also proposed a robust data-driven model based on a polyhedral uncertainty set to address the unjust worldwide vaccine distribution as an uncertain parameter. It is acceptably robust and is also less conservative than its classical counterparts. For validation, the model has been implemented in a real case in Iran, and the results have shown that it is 21% less conservative than its classical rivals (Box and Polyhedral convex uncertainty sets) in facing the uncertain parameter. As a result, the model proposes the construction of two domestic vaccine production centers, including Pasteur Institute and Razi Institute, and five foreign distributors in Tehran, Isfahan, Ahvaz, Kermanshah, and Bandar Abbas strategically. … (more)
- Is Part Of:
- Omega. Volume 110(2022)
- Journal:
- Omega
- Issue:
- Volume 110(2022)
- Issue Display:
- Volume 110, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 110
- Issue:
- 2022
- Issue Sort Value:
- 2022-0110-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07
- Subjects:
- Vaccine supply chain -- COVID-19 pandemic -- Sustainability -- Data-driven optimization -- Robust optimization -- Cutting hyperplanes
Management -- Periodicals
658.4005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/latest/03050483 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.omega.2022.102637 ↗
- Languages:
- English
- ISSNs:
- 0305-0483
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6256.426000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21222.xml