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Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients

INTRODUCTION: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) fo...

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Autores principales: Albahri, O.S., Zaidan, A.A., Albahri, A.S., Alsattar, H.A., Mohammed, Rawia, Aickelin, Uwe, Kou, Gang, Jumaah, FM., Salih, Mahmood M., Alamoodi, A.H., Zaidan, B.B., Alazab, Mamoun, Alnoor, Alhamzah, Al-Obaidi, Jameel R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378994/
https://www.ncbi.nlm.nih.gov/pubmed/35475277
http://dx.doi.org/10.1016/j.jare.2021.08.009
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author Albahri, O.S.
Zaidan, A.A.
Albahri, A.S.
Alsattar, H.A.
Mohammed, Rawia
Aickelin, Uwe
Kou, Gang
Jumaah, FM.
Salih, Mahmood M.
Alamoodi, A.H.
Zaidan, B.B.
Alazab, Mamoun
Alnoor, Alhamzah
Al-Obaidi, Jameel R.
author_facet Albahri, O.S.
Zaidan, A.A.
Albahri, A.S.
Alsattar, H.A.
Mohammed, Rawia
Aickelin, Uwe
Kou, Gang
Jumaah, FM.
Salih, Mahmood M.
Alamoodi, A.H.
Zaidan, B.B.
Alazab, Mamoun
Alnoor, Alhamzah
Al-Obaidi, Jameel R.
author_sort Albahri, O.S.
collection PubMed
description INTRODUCTION: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues. OBJECTIVES: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods. METHODS: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the ‘recipients list’ and ‘COVID-19 distribution criteria’. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM. RESULTS: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values. CONCLUSION: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide.
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spelling pubmed-83789942021-08-23 Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients Albahri, O.S. Zaidan, A.A. Albahri, A.S. Alsattar, H.A. Mohammed, Rawia Aickelin, Uwe Kou, Gang Jumaah, FM. Salih, Mahmood M. Alamoodi, A.H. Zaidan, B.B. Alazab, Mamoun Alnoor, Alhamzah Al-Obaidi, Jameel R. J Adv Res Mathematics, Engineering, and Computer Science INTRODUCTION: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues. OBJECTIVES: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods. METHODS: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the ‘recipients list’ and ‘COVID-19 distribution criteria’. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM. RESULTS: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values. CONCLUSION: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide. Elsevier 2021-08-21 /pmc/articles/PMC8378994/ /pubmed/35475277 http://dx.doi.org/10.1016/j.jare.2021.08.009 Text en © 2022 The Authors
spellingShingle Mathematics, Engineering, and Computer Science
Albahri, O.S.
Zaidan, A.A.
Albahri, A.S.
Alsattar, H.A.
Mohammed, Rawia
Aickelin, Uwe
Kou, Gang
Jumaah, FM.
Salih, Mahmood M.
Alamoodi, A.H.
Zaidan, B.B.
Alazab, Mamoun
Alnoor, Alhamzah
Al-Obaidi, Jameel R.
Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients
title Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients
title_full Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients
title_fullStr Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients
title_full_unstemmed Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients
title_short Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients
title_sort novel dynamic fuzzy decision-making framework for covid-19 vaccine dose recipients
topic Mathematics, Engineering, and Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378994/
https://www.ncbi.nlm.nih.gov/pubmed/35475277
http://dx.doi.org/10.1016/j.jare.2021.08.009
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