<p>This study aims to solve the problem of the site selection and distribution of emergency stockpiles during an epidemic outbreak. To this end, this study takes the demand prediction result of the Susceptible-Exposed-Infectious-Recovered-Dead epidemic model as the basis for site selection and constructs a double-layer model of site selection and the distribution of emergency tertiary logistics, with “strategic national stockpile–regional distribution center–demand point" as the main line. Considering the capacity limitation, coverage radius, and dispatch scheduling of different models of vehicles, the upper layer aims to minimize the sum of various types of costs, while the lower layer aims to minimize the average distribution time. Focusing on the NP-hard characteristics of the problem, based on the basic life choice–based optimizer, a nonlinear convergence factor and an enhanced search levy flight strategy are introduced to design a novel life choice–based optimizer to solve the upper layer model; the lower layer is solved using the Floyd’s algorithm. Real data for Changchun City during the Coronavirus disease 2019 epidemic in 2022 are used for empirical research. The joint optimization algorithm of the novel life choice–based optimizer and Floyd’s algorithm is compared with other algorithms. The experimental results show the feasibility of the new model and the effectiveness of the new algorithm.</p>