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Article

Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach

1
Department of Industrial Engineering and Management, Chaoyang University of Technology, Taichung 413310, Taiwan
2
Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan
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Department of Industrial Engineering and Management National Chiao Tung University 1001, University Road, Hsinchu 30010, Taiwan
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(10), 1725; https://doi.org/10.3390/math8101725
Received: 10 September 2020 / Revised: 20 September 2020 / Accepted: 26 September 2020 / Published: 7 October 2020
(This article belongs to the Special Issue Applications of Fuzzy Optimization and Fuzzy Decision Making)
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. View Full-Text
Keywords: intervention strategy; COVID-19 pandemic; layered partial consensus; fuzzy analytic hierarchy process intervention strategy; COVID-19 pandemic; layered partial consensus; fuzzy analytic hierarchy process
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MDPI and ACS Style

Wu, H.-C.; Wang, Y.-C.; Chen, T.-C.T. Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach. Mathematics 2020, 8, 1725. https://doi.org/10.3390/math8101725

AMA Style

Wu H-C, Wang Y-C, Chen T-CT. Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach. Mathematics. 2020; 8(10):1725. https://doi.org/10.3390/math8101725

Chicago/Turabian Style

Wu, Hsin-Chieh, Yu-Cheng Wang, and Tin-Chih T. Chen 2020. "Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach" Mathematics 8, no. 10: 1725. https://doi.org/10.3390/math8101725

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