The adequacy of the bandwidth is essential for delivering stable and high-quality transmission services. However, existing routing methods often rely on single transmission paths, which limit bandwidth utilization and place higher demands on routing decisions for bandwidth allocation. Small traffic flows may occupy high-capacity paths, leaving larger traffic flows unmet. To address these challenges, this paper proposes a novel routing algorithm that allocates paths based on bandwidth demands. By decomposing the routing problem through the overlay of multiple single paths, the algorithm reduces complexity. In addition, it integrates traffic splitting techniques and reinforcement learning to dynamically optimize path selection and improve performance in software-defined networks. The simulation results show that the proposed method achieves an average improvement of approximately 50.79% in system throughput compared to shortest path routing and 34.68% compared to maximum bandwidth path routing, demonstrating its effectiveness in optimizing network resource utilization.