Abstract
We propose an innovative framework to deploy a one-way Electric Vehicle (EV) sharing system that serves an urban area. For the first time, long-term infrastructure planning (charging station location and fleet distribution) and real-time fleet operations (relocation and charging decisions) are jointly optimized under time-varying uncertain demand. This substantially advances EV sharing system efficiency and yields a practical management strategy. We propose a multistage stochastic model to address the critical challenge of time-varying uncertain demand. An accelerated solution algorithm is developed to conquer the curse of dimensionality in integer infrastructure planning decisions. Meaningful insights are delivered through hypothetical numerical experiments and a realistic case study with EV sharing service in the New York City.
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