Abstract: Cooperative combat involving multiple unmanned surface vehicles (USVs) is an important development trend in future warfare, and rapid cooperative path planning will make cooperative combat possible. To address issues such as the low search efficiency and overly complicated coordination constraints of existing path planning methods caused by the difficulty in balancing coordination and speed, an initial path expression form is given based on the Voronoi diagram planning space model, the initial path cost is calculated according to the constraints, and the initial path generation process is completed based on the Voronoi diagram. Then, an evolutionary algorithm utilizing parallel computing technology is applied to search for the initial path, and a rapid path planning method for single USV is designed. Finally, combined with the multi-USV cooperative control strategy, a cooperative path that meets the constraints is provided. Simulation results show that rapid, efficient, and optimal multi-USV cooperative path planning can be realized using this algorithm. Compared with the traditional genetic algorithm, the number of evolution generations is reduced by approximately 40%, and the evolution time is decreased by about 53%.