Chance-Constrained Model for Electric Bus Scheduling

This technical report presents a novel chance-constrained model addressing the electric vehicle scheduling problem (E-VSP) with a focus on battery management strategies for electric buses (EBs). It outlines the challenges associated with the transition to EBs, including limited driving range, charging times, and battery degradation. The model incorporates stochastic energy consumption and adheres to recommended state-of-charge (SoC) ranges while optimizing operational costs. A tailored branch-and-price heuristic is developed to solve the model, and computational experiments demonstrate its effectiveness compared to deterministic approaches. The report emphasizes the importance of maintaining battery health and longevity through appropriate fleet management practices and highlights the need for operating EBs within established SoC safety ranges. Furthermore, the study addresses existing literature gaps regarding battery degradation in E-VSP, advocating for models that do not rely on specific capacity fading functions. The document concludes by summarizing the proposed methodologies and their implications for future research and practical applications in urban transportation systems.