An Integrated Framework for Optimized Cross-Line Transit Scheduling

This paper introduces a scheduling framework for reinforcement bus transit that enables targeted cross-line deployment without disrupting existing routes. Unlike conventional strategies that rely on full-line reallocation, the proposed method focuses on reinforcing high-demand segments across multiple lines. The approach consists of three key steps: identifying critical segments based on passenger volume using a graph-based network model; optimizing departure intervals via a mixed-integer programming formulation that accounts for waiting time, crowding, and operational cost; and implementing fixed scheduling for selected segments. Simulation experiments demonstrate that this method effectively reduces passenger delays, improves vehicle load balance, and lowers service deployment intensity. Under imbalanced demand conditions, the proposed framework achieves measurable reductions in both operating frequency and bus overcrowding, offering a scalable and resource-efficient alternative to traditional reinforcement practices.