Numerical Treatment for the Distributed Order Fractional Optimal Control Coronavirus (2019-nCov) Mathematical Model

Authors

  • Nehaya R. Alsenaideh Mathematics Department, Faculty of Science, Ain Shams University, Cairo, Egypt
  • Seham M. Al-Mekhlafi Mathematics Department, Faculty of Education, Sana'a University, Yemen
  • Saleh M. Hassan Mathematics Department, Faculty of Science, Ain Shams University, Cairo, Egypt
  • Abdelaziz E. Radwan Mathematics Department, Faculty of Science, Ain Shams University, Cairo, Egypt
  • Nasser H. Sweilam Mathematics Department, Faculty of Science, Cairo University, Giza, Egypt https://orcid.org/0000-0001-7428-5799

DOI:

https://doi.org/10.37256/cm.5420245129

Keywords:

coronavirus, composite simpson's rule, distributed order derivatives, Grünwald-Letnikov nonstandard finite difference method, optimal control problem

Abstract

In this paper, we presented the distributed order fractional optimal control of the Coronavirus (2019-nCov) mathematical model. The distributed order fractional operator is defined in the Caputo sense. Control variables are considered to reduce the transmission of infection to healthy people. The discretization of the composite Simpson's rule and Grünwald-Letnikov nonstandard finite difference method is constructed to solve the obtained optimality system numerically. The stability analysis of the proposed method is studied. Numerical examples and comparative studies for testing the applicability of the utilized method and to show the simplicity of this approximation approach are presented. Moreover, by using the proposed method we can conclude that the model given in this paper describes well the confirmed real data given in Spain and Wuhan.

Downloads

Published

2024-10-31

How to Cite

1.
Alsenaideh NR, Al-Mekhlafi SM, Hassan SM, Radwan AE, Sweilam NH. Numerical Treatment for the Distributed Order Fractional Optimal Control Coronavirus (2019-nCov) Mathematical Model. Contemp. Math. [Internet]. 2024 Oct. 31 [cited 2024 Nov. 7];5(4):4643-61. Available from: https://ojs.wiserpub.com/index.php/CM/article/view/5129