OPTIMAL CONTROL ANALYSIS OF A MATHEMATICAL MODEL FOR DRUG ADDICTION

Drug addiction is a serious public health epidemic with far-reaching societal, economic, and personal consequences.This paper proposes an optimal control policy for the deterministic drug addiction model.The model takes into account three state variables:suspectables (those at risk of addiction), infected (drug addicts), and recovered.The model also accounts for factors such as drug addicts' deaths, natural recovery from drug addiction, and so on.The proposed drug addiction model's optimal control analysis is carried out utilizing Pontryagin's maximum principal.The prerequisites for optimal control of the drug addiction problem are derived and analyzed using effective drug addiction control approaches.

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Publication Details

Published
2024-11-30
DOI
https://doi.org/10.71058/jodac.v8i11025
Primary Topic
Advanced Control Systems Optimization
Type
article
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article

OPTIMAL CONTROL ANALYSIS OF A MATHEMATICAL MODEL FOR DRUG ADDICTION

Prakash R Kengnal, Shankrevva R Gani
Advanced Control Systems Optimization
article

OPTIMAL CONTROL ANALYSIS OF A MATHEMATICAL MODEL FOR DRUG ADDICTION

Prakash R Kengnal, Shankrevva R Gani
article en

Abstract

Drug addiction is a serious public health epidemic with far-reaching societal, economic, and personal consequences.This paper proposes an optimal control policy for the deterministic drug addiction model.The model takes into account three state variables:suspectables (those at risk of addiction), infected (drug addicts), and recovered.The model also accounts for factors such as drug addicts' deaths, natural recovery from drug addiction, and so on.The proposed drug addiction model's optimal control analysis is carried out utilizing Pontryagin's maximum principal.The prerequisites for optimal control of the drug addiction problem are derived and analyzed using effective drug addiction control approaches.

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Advanced Control Systems Optimization
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OPTIMAL CONTROL ANALYSIS OF A MATHEMATICAL MODEL FOR DRUG ADDICTION — Prakash R Kengnal, Shankrevva R Gani · (2024) | TGRS Research Map | TGRS