Abstract
This paper introduces a dynamic model that explores smoking and optimal control strategies. It shows how fractional-order (FO) analysis has uncovered hidden parts of complex systems and provides information about previously ignored elements. This paper uses the Bernoulli wavelet operational matrix method and the Adam–Bashforth–Moulton (ABM) method to analyse this model numerically. The mathematical model is segmented into five sub-classes: susceptible smokers, ingestion class, unusual smokers, regular smokers, and ex-smokers. It considers four optimal control measures: an anti-smoking education campaign, distribution of anti-smoking gum, administration of anti-nicotine drugs, and governmental restrictions on smoking in public areas. We show in this model how to control smoking in society strategically.
| Original language | English |
|---|---|
| Article number | 583 |
| Journal | Fractal and Fractional |
| Volume | 9 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Bernoulli wavelet method
- Caputo derivative
- fractional optimum control problem (FOCP)
- fractional-order model
- operational matrix
- residual-error analysis
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