The shift towards environmentally friendly and efficient electric bus transportation systems oftentimes raises unexpected operational issues. This study models the Electric Bus Charging Station Location Problem (EB-CSLP) to develop a more resilient charging infrastructure, focusi
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The shift towards environmentally friendly and efficient electric bus transportation systems oftentimes raises unexpected operational issues. This study models the Electric Bus Charging Station Location Problem (EB-CSLP) to develop a more resilient charging infrastructure, focusing on time-related and energy consumption uncertainties, specifically inter-station travel time delays. The model accommodates various charger types and maintains time continuity in the charging of electric buses. Initially formulated as a mixed-integer nonlinear program (MINLP), our stochastic optimization model is reformulated into a mixed-integer linear program (MILP) which minimizes both deadheading times and queue waiting times at the charging locations. The stochastic optimization model is tested in a real-world case study in Athens, Greece, considering multiple scenarios with varying inter-station travel times and energy consumption. The results demonstrate its effectiveness as a potential decision-support tool for selecting the optimal charger types and charging station locations under travel time and energy-related uncertainties.