{"title":"Optimal control of a diffusive epidemiological model involving the Caputo–Fabrizio fractional time-derivative","authors":"Achraf Zinihi , Moulay Rchid Sidi Ammi , Matthias Ehrhardt","doi":"10.1016/j.padiff.2025.101188","DOIUrl":null,"url":null,"abstract":"<div><div>In this work we study a fractional SEIR biological model of a reaction–diffusion, using the non-singular kernel Caputo–Fabrizio fractional derivative in the Caputo sense and employing the Laplacian operator. In our PDE model, the government seeks immunity through the vaccination program, which is considered a control variable. Our study aims to identify the ideal control pair that reduces the number of infected/infectious people and the associated vaccine and treatment costs over a limited time and space. Moreover, by using the forward–backward algorithm, the approximate results are explained by dynamic graphs to monitor the effectiveness of vaccination.</div></div>","PeriodicalId":34531,"journal":{"name":"Partial Differential Equations in Applied Mathematics","volume":"14 ","pages":"Article 101188"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Partial Differential Equations in Applied Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666818125001159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
In this work we study a fractional SEIR biological model of a reaction–diffusion, using the non-singular kernel Caputo–Fabrizio fractional derivative in the Caputo sense and employing the Laplacian operator. In our PDE model, the government seeks immunity through the vaccination program, which is considered a control variable. Our study aims to identify the ideal control pair that reduces the number of infected/infectious people and the associated vaccine and treatment costs over a limited time and space. Moreover, by using the forward–backward algorithm, the approximate results are explained by dynamic graphs to monitor the effectiveness of vaccination.