Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach
The COVID-19 pandemic has severely impacted our daily lives. For tackling the COVID-19 pandemic, various intervention strategies have been adopted by country (or city) governments around the world. However, whether an intervention strategy will be successful, acceptable, and cost-effective or not is...
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| Format: | Article |
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MDPI AG
2020-10-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/8/10/1725 |
| _version_ | 1797551630336393216 |
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| author | Hsin-Chieh Wu Yu-Cheng Wang Tin-Chih Toly Chen |
| author_facet | Hsin-Chieh Wu Yu-Cheng Wang Tin-Chih Toly Chen |
| author_sort | Hsin-Chieh Wu |
| collection | DOAJ |
| description | The COVID-19 pandemic has severely impacted our daily lives. For tackling the COVID-19 pandemic, various intervention strategies have been adopted by country (or city) governments around the world. However, whether an intervention strategy will be successful, acceptable, and cost-effective or not is still questionable. To address this issue, a varying partial consensus fuzzy collaborative intelligence approach is proposed in this study to assess an intervention strategy. In the varying partial consensus fuzzy collaborative intelligence approach, multiple decision makers express their judgments on the relative priorities of factors critical to an intervention strategy. If decision makers lack an overall consensus, the layered partial consensus approach is applied to aggregate their judgments for each critical factor. The number of decision makers that reach a partial consensus varies from a critical factor to another. Subsequently, the generalized fuzzy weighted assessment approach is proposed to evaluate the overall performance of an intervention strategy for tackling the COVID-19 pandemic. The proposed methodology has been applied to compare 15 existing intervention strategies for tackling the COVID-19 pandemic. |
| first_indexed | 2024-03-10T15:48:51Z |
| format | Article |
| id | doaj.art-774be1a9e2644519bb439c04a58122e1 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T15:48:51Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-774be1a9e2644519bb439c04a58122e12023-11-20T16:16:10ZengMDPI AGMathematics2227-73902020-10-01810172510.3390/math8101725Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence ApproachHsin-Chieh Wu0Yu-Cheng Wang1Tin-Chih Toly Chen2Department of Industrial Engineering and Management, Chaoyang University of Technology, Taichung 413310, TaiwanDepartment of Aeronautical Engineering, Chaoyang University of Technology, Taichung 413310, TaiwanDepartment of Industrial Engineering and Management National Chiao Tung University 1001, University Road, Hsinchu 30010, TaiwanThe COVID-19 pandemic has severely impacted our daily lives. For tackling the COVID-19 pandemic, various intervention strategies have been adopted by country (or city) governments around the world. However, whether an intervention strategy will be successful, acceptable, and cost-effective or not is still questionable. To address this issue, a varying partial consensus fuzzy collaborative intelligence approach is proposed in this study to assess an intervention strategy. In the varying partial consensus fuzzy collaborative intelligence approach, multiple decision makers express their judgments on the relative priorities of factors critical to an intervention strategy. If decision makers lack an overall consensus, the layered partial consensus approach is applied to aggregate their judgments for each critical factor. The number of decision makers that reach a partial consensus varies from a critical factor to another. Subsequently, the generalized fuzzy weighted assessment approach is proposed to evaluate the overall performance of an intervention strategy for tackling the COVID-19 pandemic. The proposed methodology has been applied to compare 15 existing intervention strategies for tackling the COVID-19 pandemic.https://www.mdpi.com/2227-7390/8/10/1725intervention strategyCOVID-19 pandemiclayered partial consensusfuzzy analytic hierarchy process |
| spellingShingle | Hsin-Chieh Wu Yu-Cheng Wang Tin-Chih Toly Chen Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach Mathematics intervention strategy COVID-19 pandemic layered partial consensus fuzzy analytic hierarchy process |
| title | Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach |
| title_full | Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach |
| title_fullStr | Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach |
| title_full_unstemmed | Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach |
| title_short | Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach |
| title_sort | assessing and comparing covid 19 intervention strategies using a varying partial consensus fuzzy collaborative intelligence approach |
| topic | intervention strategy COVID-19 pandemic layered partial consensus fuzzy analytic hierarchy process |
| url | https://www.mdpi.com/2227-7390/8/10/1725 |
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