Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect

This work presents a novel evolutionary computation-based Padé approximation (EPA) scheme for constructing a closed-form approximate solution of a nonlinear dynamical model of Covid-19 disease with a crowding effect that is a growing trend in epidemiological modeling. In the proposed framework of th...

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Autores principales:	Javaid Ali, Ali Raza, Nauman Ahmed, Ali Ahmadian, Muhammad Rafiq, Massimiliano Ferrara
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Evolutionary computing Padé approximation Covid-19 model Crowding effect Hybrid optimizer Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/2a8c5abc074c4958a60bb916f7f2910c
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spelling	oai:doaj.org-article:2a8c5abc074c4958a60bb916f7f2910c2021-12-04T04:34:21ZEvolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect2214-716010.1016/j.orp.2021.100207https://doaj.org/article/2a8c5abc074c4958a60bb916f7f2910c2021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2214716021000245https://doaj.org/toc/2214-7160This work presents a novel evolutionary computation-based Padé approximation (EPA) scheme for constructing a closed-form approximate solution of a nonlinear dynamical model of Covid-19 disease with a crowding effect that is a growing trend in epidemiological modeling. In the proposed framework of the EPA scheme, the crowding effect-driven system is transformed to an equivalent nonlinear global optimization problem by assimilating Padé rational functions. The initial conditions, boundedness, and positivity of the solution are dealt with as problem constraints. Keeping in view the complexity of formulated optimization problem, a hybrid of differential evolution (DE) and a convergent variant of the Nelder-Mead Simplex algorithm is also proposed to obtain a reliable, optimal solution. The comparison of the EPA scheme results reveals that optimization results of all formulated optimization problems for the Covid-19 model with crowding effect are better than those of several modern metaheuristics. EPA-based solutions of the Covid-19 model with crowding effect are in good agreement with those of a well-practiced nonstandard finite difference (NSFD) scheme. The proposed EPA scheme is less sensitive to step lengths and converges to true equilibrium points unconditionally.Javaid AliAli RazaNauman AhmedAli AhmadianMuhammad RafiqMassimiliano FerraraElsevierarticleEvolutionary computingPadé approximationCovid-19 modelCrowding effectHybrid optimizerMathematicsQA1-939ENOperations Research Perspectives, Vol 8, Iss , Pp 100207- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Evolutionary computing Padé approximation Covid-19 model Crowding effect Hybrid optimizer Mathematics QA1-939
spellingShingle	Evolutionary computing Padé approximation Covid-19 model Crowding effect Hybrid optimizer Mathematics QA1-939 Javaid Ali Ali Raza Nauman Ahmed Ali Ahmadian Muhammad Rafiq Massimiliano Ferrara Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect
description	This work presents a novel evolutionary computation-based Padé approximation (EPA) scheme for constructing a closed-form approximate solution of a nonlinear dynamical model of Covid-19 disease with a crowding effect that is a growing trend in epidemiological modeling. In the proposed framework of the EPA scheme, the crowding effect-driven system is transformed to an equivalent nonlinear global optimization problem by assimilating Padé rational functions. The initial conditions, boundedness, and positivity of the solution are dealt with as problem constraints. Keeping in view the complexity of formulated optimization problem, a hybrid of differential evolution (DE) and a convergent variant of the Nelder-Mead Simplex algorithm is also proposed to obtain a reliable, optimal solution. The comparison of the EPA scheme results reveals that optimization results of all formulated optimization problems for the Covid-19 model with crowding effect are better than those of several modern metaheuristics. EPA-based solutions of the Covid-19 model with crowding effect are in good agreement with those of a well-practiced nonstandard finite difference (NSFD) scheme. The proposed EPA scheme is less sensitive to step lengths and converges to true equilibrium points unconditionally.
format	article
author	Javaid Ali Ali Raza Nauman Ahmed Ali Ahmadian Muhammad Rafiq Massimiliano Ferrara
author_facet	Javaid Ali Ali Raza Nauman Ahmed Ali Ahmadian Muhammad Rafiq Massimiliano Ferrara
author_sort	Javaid Ali
title	Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect
title_short	Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect
title_full	Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect
title_fullStr	Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect
title_full_unstemmed	Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect
title_sort	evolutionary optimized padé approximation scheme for analysis of covid-19 model with crowding effect
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/2a8c5abc074c4958a60bb916f7f2910c
work_keys_str_mv	AT javaidali evolutionaryoptimizedpadeapproximationschemeforanalysisofcovid19modelwithcrowdingeffect AT aliraza evolutionaryoptimizedpadeapproximationschemeforanalysisofcovid19modelwithcrowdingeffect AT naumanahmed evolutionaryoptimizedpadeapproximationschemeforanalysisofcovid19modelwithcrowdingeffect AT aliahmadian evolutionaryoptimizedpadeapproximationschemeforanalysisofcovid19modelwithcrowdingeffect AT muhammadrafiq evolutionaryoptimizedpadeapproximationschemeforanalysisofcovid19modelwithcrowdingeffect AT massimilianoferrara evolutionaryoptimizedpadeapproximationschemeforanalysisofcovid19modelwithcrowdingeffect
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Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect

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