To address the challenge of mission planning for multi-rover cooperative exploration on the lunar, a Multi-Traveling Salesman Problem (MTSP) model for multi-rover cooperative mission planning has been formulated. Subsequently, a solution methodology tailored for cooperative detection tasks based on the lunar road network has been proposed. To quantify the operational efficiency, a lunar detection time network was constructed, taking into account the rover’s speed, travel time, detection time, and charging time. To tackle the MTSP under the constraints imposed by this lunar detection time network, a partheno-genetic algorithm (PGA) was employed. Furthermore, an analysis was conducted to examine the impact of varying the number of rovers and the departure time intervals on the planning outcomes. The results demonstrate that the proposed model and algorithm are effective in resolving the multi-rover mission planning problems.