Work

Coronavirus Metamorphosis Optimization Algorithm and Collocation Method for Optimal Control Problem in COVID‐19 Vaccination Model

Year: 2024

Type: article

Abstract: ABSTRACT This article addresses an optimal control problem (OCP) related to the COVID‐19 vaccination model. We transform the OCP into a nonlinear programming (NLP) problem by employing a collocation method that utilizes shifted Jacobian polynomials (SJPs) and their derivative operational matrices. To solve the NLP, we implement the Coronavirus Metamorphosis Optimization Algorithm (CMOA), which determines the control variables for , 2, and 3, corresponding to isolation, vaccination efficacy, and treatment enhancement. The CMOA is particularly suitable for the OCP concerning COVID‐19 due to its ability to navigate complex challenges and provide accurate solutions. Therefore, the primary aim of this paper is to identify a high‐quality optimal solution for the OCP, thereby contributing to the development of effective control strategies for managing the COVID‐19 pandemic.

Source: Optimal Control Applications and Methods

DOI: 10.1002/oca.3215

Authors: A. Jajarmi, A. Ebrahimzadeh, R. Khanduzi

Institutions: University of Bojnord, Farhangian University, Gonbad Kavous University

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: Farhangian University