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RESEARCH ARTICLE

Collocation method with flood-based metaheuristic optimizer for optimal control on a multi-strain COVID-19 model

Asiyeh Ebrahimzadeh1 ,  Raheleh Khanduzi2* ,  Amin Jajarmi3,4*
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1 Department of Mathematics Education, Farhangian University, P.O. Box, 14665-889, Tehran, Iran
2 Department of Mathematics and Statistics, Gonbad Kavous University, P. O. Box, 49771-99151, Gonbad Kavous, Iran
3 Department of Electrical Engineering, University of Bojnord, P.O. Box, 94531-1339, Bojnord, Iran
4 Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 602105, Tamil Nadu, India
IJOCTA 2025, 15(2), 93–109; https://doi.org/10.36922/ijocta.1735
Received: 17 November 2024 | Accepted: 19 February 2025 | Published online: 4 April 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

This paper describes a new and powerful way to solve optimal control problems (OCPs) on a multi-strain COVID-19 model for strategies related to vaccination and amplification. We call it the collocation method with a flood-based metaheuristic optimizer (FBMO). We use a collocation method with Laguerre polynomials and their derivative operational matrices to turn the OCP into a nonlinear programming (NLP) problem. To address the NLP, the research employs the FBMO to determine the control variables ui for i = 1, 2, and 3, representing isolation, vaccination efficacy, and treatment enhancement, in conjunction with the state function of the multi-strain COVID-19 model. These strategies are executed within an SVIcIvR-type control model for COVID-19 in Morocco, designed to control the outbreak of multi-strain disease. The paper’s primary aim is to achieve a high-quality optimal solution for the given OCP, thereby contributing to the advancement of efficient strategies for managing the COVID-19 pandemic.

Keywords
Multi-strain
Amplification
Optimal control
Vaccination
Collocation method
Flood-based metaheuristic optimizer
Funding
This work has financial support of Farhangian University (Contract No. 500.17474.120).
Conflict of interest
The authors declare that they have no conflict of interest regarding the publication of this article.
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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing
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