Version 1
: Received: 26 October 2023 / Approved: 26 October 2023 / Online: 27 October 2023 (12:55:48 CEST)
How to cite:
Wang, Z.; Wen, X.; Lu, Z. Global Optimization Theories and Techniques for COVID-19. Preprints2023, 2023101810. https://doi.org/10.20944/preprints202310.1810.v1
Wang, Z.; Wen, X.; Lu, Z. Global Optimization Theories and Techniques for COVID-19. Preprints 2023, 2023101810. https://doi.org/10.20944/preprints202310.1810.v1
Wang, Z.; Wen, X.; Lu, Z. Global Optimization Theories and Techniques for COVID-19. Preprints2023, 2023101810. https://doi.org/10.20944/preprints202310.1810.v1
APA Style
Wang, Z., Wen, X., & Lu, Z. (2023). Global Optimization Theories and Techniques for COVID-19. Preprints. https://doi.org/10.20944/preprints202310.1810.v1
Chicago/Turabian Style
Wang, Z., Xin Wen and Zhihai Lu. 2023 "Global Optimization Theories and Techniques for COVID-19" Preprints. https://doi.org/10.20944/preprints202310.1810.v1
Abstract
As the COVID-19 pandemic has caused enormous damage to society, economy and public health security, it is crucial to combat the epidemic and allocate social and health resources effectively. Global optimization algorithms are extensively used in many domains to find optimal solutions to complex problems. Thus, a survey of three typical global optimizations applied on the COVID-19 pandemic is timely. This article is structured into three typical global optimization algorithms - Genetic Algorithm, Particle Swarm Optimization, and Cat Swarm Optimization - and summarizes the framework models and practical applications, as well as other optimization methods that may be applied to COVID-19. Finally, current unresolved challenges and future research opportunities to be explored are summarized.
Medicine and Pharmacology, Epidemiology and Infectious Diseases
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
