Abstract: To address the limitations of current multi-UAV deployment optimization algorithms in terms of coverage efficiency, this paper proposes a UAV deployment optimization algorithm based on Voronoi partitioning (VP) and virtual force (VVF). Specifically, the algorithm first divides the target area into multiple sub-regions using Voronoi partitioning based on an initial random deployment, and constructs a local coverage model for each sub-region. Then, in each local coverage model, the algorithm uses an improved virtual force mechanism to adjust the UAV positions and efficiently eliminate coverage holes. Finally, the current deployment result is evaluated, and redundant UAVs are removed. Compared with the edge virtual force (EVF) algorithm, the vertex-edge virtual force (VEVF) algorithm, and the particle swarm optimization and Voronoi diagram (PSOVD) algorithm, the proposed VVF achieves a maximum improvement of 9.32% in coverage efficiency. In addition, compared with the particle swarm optimization (PSO) algorithm and the artificial bee colony (ABC) algorithm, VVF improves execution efficiency by up to 31.26%.