USE OF EVOLUTIONARY ALGORITHMS IN A FRACTIONAL FRAMEWORK TO PREVENT THE SPREAD OF CORONAVIRUS

Bo Wang, Hadi Jahanshahi (), Yeliz Karaca (), Stelios Bekiros, Wei-Feng Xia, Abdulhameed F. Alkhateeb () and Majid Nour ()
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Bo Wang: School of Electronic Information and Automation, Aba Teachers University, Wenchuan 623002, P. R. China†School of Applied Mathematics, University Electronic Science and Technology of China, Chengdu 610054, P. R. China
Hadi Jahanshahi: ��Department of Mechanical Engineering, University of Manitoba, Winnipeg, Canada R3T 5V6, Canada
Yeliz Karaca: �University of Massachusetts Medical School, Worcester, MA 01655, USA
Wei-Feng Xia: *School of Engineering, Huzhou University, Huzhou 313000, P. R. China††Institute for Advanced Study Honoring Chen Jian Gong, Hangzhou Normal University, Hangzhou 311121, P. R. China
Abdulhameed F. Alkhateeb: ��‡Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
Majid Nour: ��‡Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia

FRACTALS (fractals), 2022, vol. 30, issue 05, 1-14

Abstract: Mathematical modeling can be utilized to find out how the coronavirus spreads within a population. Hence, considering models that can precisely describe natural phenomena is of crucial necessity. Besides, although one of the most significant benefits of mathematical modeling is designing optimal policies for battling the disease, there are a few studies that employ this beneficial aspect. To this end, this study aims to design optimal management policies for the novel coronavirus disease 2019 (COVID-19). This is a pioneering research that designs optimal policies based on multi-objective evolutionary algorithms for control of the fractional-order model of the COVID-19 outbreak. First, a fractional-order model of the disease dynamic is presented. The impacts of the fractional derivative’s value on the modeling and forecasting of the disease spread are considered. After that, a multi-objective optimization problem is proposed by considering the rate of communication, the transition of symptomatic infected class to the quarantined one, and the release of quarantined uninfected individuals. Numerical results clearly corroborate that by solving the proposed multi-objective problem, governments can control the massive disease outbreak while economic factors have reasonable values that prevent economic collapse.

Keywords: Novel Coronavirus; COVID-19; Fractional-Order Mathematical Model; Control of Epidemics (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X22401466

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