Abstract
One-way electric vehicle (EV) sharing systems have received increasing attention because of their environmental, mobility, and societal benefits. In this research, we investigate the vehicle deployment and relocation problem for hybrid one-way station-based and free-floating electric vehicle sharing systems considering demand and parking space stochasticity. The problem is formulated as a two-stage stochastic program. In the first stage, the EVs are deployed into a sharing system based on historical customer data to maximize the resulting profit. The second stage maximizes the expected profit by relocating the EVs in the system using relocation staff in response to an uncertain demand. To solve the resulting complicated problem, an integer L-shaped method is proposed so that the cuts can efficiently fathom the solution space and identify solutions with a reasonable optimality gap. The proposed solution framework is empirically applied to cases of various sizes. The empirical results demonstrate the effectiveness of the proposed solution scheme.
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