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.
ABSTRACT
Firstly, in the present study, classical and fractional variants modeling of the new coronavirus disease transmission are numerically investigated. Afterward, to shape robust and effective policies for preventing the massive outbreak, a fuzzy-based sliding mode control technique is designed. The contact rate is considered as governmental control action, and a robust and effective policy is proposed while its stability and convergence are proven. The numerical simulations of the proposed scenario for two different conditions are demonstrated. It is confirmed through numerical simulation that it is possible to reduce the total number of infected and exposed cases, respectively, to less than 2% and 0.5% Also, the performance of the offered technique with and without the fuzzy logic engine is investigated. This way, it is conspicuously shown that the proposed technique is able to effectively prevent a massive outbreak and keep the 2019-nCov spread in check.