Abstract: To address the limited endurance of unmanned aerial vehicles (UAVs) and the prolonged mission duration in wide-area transmission line inspection, an improved simulated annealing algorithm integrating K-means++ clustering and the Or-opt operator is proposed, with the objective of minimizing the total mission time of the UAV cluster. First, K-means++ is employed to achieve balanced clustering of transmission towers, effectively mitigating load imbalance among UAVs caused by the elongated layout of power lines. Subsequently, the Or-opt neighborhood search strategy is introduced to enhance the simulated annealing algorithm, improving global search capability while eliminating path crossings. Simulation results demonstrate that, compared with standard SA, 2-opt*-SA, and 3-opt-SA, the proposed method significantly reduces charging frequency and total inspection mileage, achieving a 68% reduction in total mileage over 2-opt*-SA, thereby confirming its effectiveness in shortening mission duration.