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Finite horizon optimal control of reaction-diffusion SIV epidemic system with stochastic environment (2401.11744v1)

Published 22 Jan 2024 in math.OC and math.DS

Abstract: This contribution mainly focuses on the finite horizon optimal control problems of a susceptible-infected-vaccinated(SIV) epidemic system governed by reaction-diffusion equations and Markov switching. Stochastic dynamic programming is employed to find the optimal vaccination effort and economic return for a stochastic reaction diffusion SIV epidemic model. To achieve this, a key step is to show the existence and uniqueness of invariant measure for the model. Then, we obtained the necessary and sufficient conditions for the near-optimal control. Furthermore, we give an algorithm to approximate the Hamilton-Jacobi BeLLMan (HJB) equation. Finally, some numerical simulations are presented to confirm our analytic results.

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