COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia
Crisis-induced vaccine supply chain management has recently drawn attention to the importance of immediate responses to a crisis (e.g., the COVID-19 pandemic). This study develops a queuing model for a crisis-induced vaccine supply chain to ensure efficient coordination and distribution of different COVID-19 vaccine types to people with various levels of vulnerability. The authors define a utility function for queues to study the changes in arrival rates related to the inventory level of vaccines, the efficiency of vaccines, and a risk aversion coefficient for vaccinees. A multi-period queuing model considering congestion in the vaccination process is proposed to minimise two contradictory objectives: (i) the expected average wait time of vaccinees and (ii) the total investment in the holding and ordering of vaccines. To develop the bi-objective non-linear programming model, the goal attainment algorithm and the non-dominated sorting genetic algorithm (NSGA-II) are employed for small- to large-scale problems. Several solution repairs are also implemented in the classic NSGA-II algorithm to improve its efficiency. Four standard performance metrics are used to investigate the algorithm. The non-parametric Friedman and Wilcoxon signed-rank tests are applied on several numerical examples to ensure the privilege of the improved algorithm. The NSGA-II algorithm surveys an authentic case study in Australia, and several scenarios are created to provide insights for an efficient vaccination program.
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- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
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Supplemental Notes:
- © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Jahani, Hamed
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0000-0002-7091-6060
- Chaleshtori, Amir Eshaghi
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0000-0002-5495-5748
- Khaksar, Seyed Mohammad Sadegh
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0000-0003-4895-9045
- Aghaie, Abdollah
- Sheu, Jiuh-Biing
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0000-0002-8007-619X
- Publication Date: 2022-7
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References; Tables;
- Pagination: 102749
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Serial:
- Transportation Research Part E: Logistics and Transportation Review
- Volume: 163
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 1366-5545
- Serial URL: http://www.sciencedirect.com/science/journal/13665545
Subject/Index Terms
- TRT Terms: Crisis management; Disaster relief; Logistics; Medical treatment; Queuing; Supply chain management
- Subject Areas: Freight Transportation; Planning and Forecasting; Security and Emergencies;
Filing Info
- Accession Number: 01850266
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 27 2022 5:19PM