Abstract Efficient vaccination planning poses a critical challenge in public health, necessitating the integration of various complex factors such as facility management, recipient assignment, inventory control, and vehicle routing. In this paper, we address this challenge by formulating the multi‐period vaccination planning problem as a mixed‐integer linear programming model aimed at minimizing total costs. To tackle this problem effectively, we introduce a novel three‐stage hybrid matheuristic (TSHM), which comprises three sequential stages. In the first stage, we simplify the problem complexity by relaxing intricate routing variables and solving a lot‐sizing problem with approximate visiting costs. The second stage refines the solution obtained in the initial stage by solving vehicle routing problems. In the third stage, a route‐based model is solved to further enhance the solution quality. We conduct extensive numerical experiments on 160 instances to evaluate the performance of the proposed TSHM approach. Results demonstrate that TSHM consistently outperforms the state‐of‐the‐art commercial solver CPLEX in both solution quality and computational efficiency. Notably, TSHM successfully solves all instances, including large‐sized ones where CPLEX fails. Furthermore, we present a case study based on real‐world data to validate the effectiveness of our proposed method in achieving a balance between completing vaccination tasks and enhancing cost‐efficiency.
Li et al. (Sat,) studied this question.