Robust scheduling strategies of electric buses under stochastic traffic conditions

The electric bus scheduling problem requires not only satisfying timetable constraints but also considering battery range limitation and vehicles' recharging plans. This paper is devoted to proposing robust scheduling strategies of electric buses to tackle the challenge brought by the stochasticity of urban traffic conditions. To avoid en-route breakdown of electric buses, reduce delay costs, and achieve robustness, we propose both static and dynamic scheduling models. The static model introduces a buffer-distance strategy to tackle the adverse impacts caused by trip time stochasticity, whereas the dynamic model takes advantage of continuously-updated road traffic conditions and periodically reschedules an electric bus fleet during a day's operations. A branch-and-price framework is extended to effectively solve both models. Using the realistic operations data of bus lines in Beijing, we conduct numerical examples to simulate the performances of the proposed models and derive some important insights. As suggested by the numerical results, the proposed models can effectively avoid en-route breakdown, while maintaining cost efficiency.