2017/09/27 by Yingdong Lu, Lu, Yingdong, Mark S. Squillante +3
Mathematics · Medicine · #COVID-19 epidemiological studies #FOS: Mathematics #Mathematical Biology Tumor Growth #Mathematical and Theoretical Epidemiology and Ecology Models #Optimization and Control (math.OC) #math.OC
paper · pdf · doi:10.48550/arxiv.1709.10345
arXiv admin note: substantial text overlap with arXiv:1709.07988
arxiv created 2017/09/27 · openalex publication_date 2017/09/27 · arxiv updated 2017/10/02 · openalex created_date 2017/10/20 · openalex updated_date 2026/07/28
The optimal control of epidemic-like stochastic processes is important both historically and for emerging applications today, where it can be especially important to include time-varying parameters that impact viral epidemic-like propagation. We connect the control of such stochastic processes with time-varying behavior to the stochastic shortest path problem and obtain solutions for various cost functions. Then, under a mean-field scaling, this general class of stochastic processes is shown to converge to a corresponding dynamical system. We analogously establish that the optimal control of this class of processes converges to the optimal control of the limiting dynamical system. Consequently, we study the optimal control of the dynamical system where the comparison of both controlled systems renders various important mathematical properties of interest.