Abstract
This study aimed to investigate optimal strategies in dynamic models of smoking. The smoking dynamic model is divided into 3 subpopulations including potential smokers (non-smokers), active smokers who smoke daily, and people who have quit smoking permanently. There are five variables of the smoking dynamic model control strategy, including education related to the dangers of smoking for health, vaccination, tobacco taxation, treatment, and rehabilitation. In solving optimization problems, this study uses the Maximum Pontryagin Principle method. Furthermore, the 4th-order runge kutta method was used to implement numerical solutions and Matlab Software to simulate a control model of smoking dynamics. Based on the simulation results, it can be seen that the control provided is effective in reducing the number of smokers and increasing the number of people who quit smoking.
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